{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "266461e7",
   "metadata": {},
   "source": [
    "# [bokeh用户指南](https://docs.bokeh.org/en/latest/docs/user_guide.html#userguide)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c2f4c74f",
   "metadata": {},
   "source": [
    "<table>\n",
    "    <tr style=\"align:center\">\n",
    "        <td>接口</td> \n",
    "        <td>用途</td> \n",
    "        <td>接口</td> \n",
    "        <td>用途</td> \n",
    "   </tr>\n",
    "    <tr align=\"center\">\n",
    "  \t\t<td>bokeh.models</td> \n",
    "        <td>设置工具条、控制、图形样式属性及绘图数据等</td> \n",
    "        <td>bokeh.plotting</td> \n",
    "        <td>围绕figure()命令，绘制基本图形，如circle，wedge等</td> \n",
    "    </tr>\n",
    "    <tr>\n",
    "        <td>bokeh.layouts</td> \n",
    "        <td>图形显示方式，如row(),column(),grid(),gridplot()等</td> \n",
    "        <td>bokeh.io</td>\n",
    "        <td>图形保存或显示模式</td> \n",
    "    </tr>\n",
    "        <tr >\n",
    "        <td>bokeh.palettes</td> \n",
    "        <td>bokeh内置调色板</td> \n",
    "        <td>bokeh.settings</td> \n",
    "        <td>控制资源消耗、日志级别等</td> \n",
    "   </tr>\n",
    "</table>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dd937af5",
   "metadata": {},
   "source": [
    "> 1. 先找到bokeh中的接口（例如models,plotting等）  \n",
    "> 2. 来找具体的子类，例如 bokeh.models.glyphs  \n",
    "> 3. 找到对应的函数方法，例如 bokeh.models.glyphs.line(),考虑使用是所需要的参（**kwargs）-->key=value主要接口"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f4e962a7",
   "metadata": {},
   "source": [
    "## 寻找接口对应的子类及其函数方法"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "529b2d83",
   "metadata": {},
   "outputs": [],
   "source": [
    "import bokeh.models"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "41255906",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on package bokeh.models in bokeh:\n",
      "\n",
      "NAME\n",
      "    bokeh.models - Provide Bokeh model \"building block\" classes.\n",
      "\n",
      "DESCRIPTION\n",
      "    One of the central design principals of Bokeh is that, regardless of\n",
      "    how the plot creation code is spelled in Python (or other languages),\n",
      "    the result is an object graph that encompasses all the visual and\n",
      "    data aspects of the scene. Furthermore, this *scene graph* is to be\n",
      "    serialized, and it is this serialized graph that the client library\n",
      "    BokehJS uses to render the plot. The low-level objects that comprise\n",
      "    a Bokeh scene graph are called :ref:`Models <bokeh.model>`.\n",
      "\n",
      "PACKAGE CONTENTS\n",
      "    annotations\n",
      "    arrow_heads\n",
      "    axes\n",
      "    callbacks\n",
      "    canvas\n",
      "    css\n",
      "    dom\n",
      "    expressions\n",
      "    filters\n",
      "    formatters\n",
      "    glyph\n",
      "    glyphs\n",
      "    graphs\n",
      "    grids\n",
      "    labeling\n",
      "    layouts\n",
      "    map_plots\n",
      "    mappers\n",
      "    markers\n",
      "    plots\n",
      "    ranges\n",
      "    renderers\n",
      "    scales\n",
      "    selections\n",
      "    sources\n",
      "    text\n",
      "    textures\n",
      "    tickers\n",
      "    tiles\n",
      "    tools\n",
      "    transforms\n",
      "    util (package)\n",
      "    widgets (package)\n",
      "\n",
      "SUBMODULES\n",
      "    buttons\n",
      "    groups\n",
      "    icons\n",
      "    inputs\n",
      "    markups\n",
      "    panels\n",
      "    sliders\n",
      "    tables\n",
      "    widget\n",
      "\n",
      "DATA\n",
      "    annotations = _Feature((3, 7, 0, 'beta', 1), (4, 0, 0, 'alpha', 0), 10...\n",
      "    log = <Logger bokeh.models.widgets (WARNING)>\n",
      "\n",
      "FILE\n",
      "    c:\\programdata\\anaconda3\\lib\\site-packages\\bokeh\\models\\__init__.py\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(bokeh.models)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1d341d5d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on module bokeh.models.filters in bokeh.models:\n",
      "\n",
      "NAME\n",
      "    bokeh.models.filters\n",
      "\n",
      "DESCRIPTION\n",
      "    #-----------------------------------------------------------------------------\n",
      "    # Copyright (c) 2012 - 2021, Anaconda, Inc., and Bokeh Contributors.\n",
      "    # All rights reserved.\n",
      "    #\n",
      "    # The full license is in the file LICENSE.txt, distributed with this software.\n",
      "    #-----------------------------------------------------------------------------\n",
      "\n",
      "CLASSES\n",
      "    bokeh.model.model.Model(bokeh.core.has_props.HasProps, bokeh.model.util.HasDocumentRef, bokeh.util.callback_manager.PropertyCallbackManager, bokeh.util.callback_manager.EventCallbackManager)\n",
      "        Filter\n",
      "            BooleanFilter\n",
      "            CustomJSFilter\n",
      "            GroupFilter\n",
      "            IndexFilter\n",
      "    \n",
      "    class BooleanFilter(Filter)\n",
      "     |  BooleanFilter(*args, **kwargs) -> 'Model'\n",
      "     |  \n",
      "     |  A ``BooleanFilter`` filters data by returning the subset of data corresponding to indices\n",
      "     |  where the values of the booleans array is True.\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      BooleanFilter\n",
      "     |      Filter\n",
      "     |      bokeh.model.model.Model\n",
      "     |      bokeh.core.has_props.HasProps\n",
      "     |      bokeh.model.util.HasDocumentRef\n",
      "     |      bokeh.util.callback_manager.PropertyCallbackManager\n",
      "     |      bokeh.util.callback_manager.EventCallbackManager\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __init__(self, *args, **kw) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  booleans\n",
      "     |      A list of booleans indicating which rows of data to select.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __overridden_defaults__ = {}\n",
      "     |  \n",
      "     |  __properties__ = {'booleans': <bokeh.core.property.nullable.Nullable o...\n",
      "     |  \n",
      "     |  __qualified_model__ = 'BooleanFilter'\n",
      "     |  \n",
      "     |  __view_model__ = 'BooleanFilter'\n",
      "     |  \n",
      "     |  __view_module__ = 'bokeh.models.filters'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __repr__ = __str__(self) -> 'str'\n",
      "     |  \n",
      "     |  __str__(self) -> 'str'\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  destroy(self) -> 'None'\n",
      "     |      Clean up references to the document and property\n",
      "     |  \n",
      "     |  js_link(self, attr: 'str', other: 'Model', other_attr: 'str', attr_selector: 'int | str | None' = None) -> 'None'\n",
      "     |      Link two Bokeh model properties using JavaScript.\n",
      "     |      \n",
      "     |      This is a convenience method that simplifies adding a CustomJS callback\n",
      "     |      to update one Bokeh model property whenever another changes value.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |      \n",
      "     |          attr (str) :\n",
      "     |              The name of a Bokeh property on this model\n",
      "     |      \n",
      "     |          other (Model):\n",
      "     |              A Bokeh model to link to self.attr\n",
      "     |      \n",
      "     |          other_attr (str) :\n",
      "     |              The property on ``other`` to link together\n",
      "     |      \n",
      "     |          attr_selector (Union[int, str]) :\n",
      "     |              The index to link an item in a subscriptable ``attr``\n",
      "     |      \n",
      "     |      Added in version 1.1\n",
      "     |      \n",
      "     |      Raises:\n",
      "     |      \n",
      "     |          ValueError\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          This code with ``js_link``:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              select.js_link('value', plot, 'sizing_mode')\n",
      "     |      \n",
      "     |          is equivalent to the following:\n",
      "     |      \n",
      "     |          .. code:: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              select.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot),\n",
      "     |                           code=\"other.sizing_mode = this.value\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |      \n",
      "     |          Additionally, to use attr_selector to attach the left side of a range slider to a plot's x_range:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)\n",
      "     |      \n",
      "     |          which is equivalent to:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              range_slider.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot.x_range),\n",
      "     |                           code=\"other.start = this.value[0]\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |  \n",
      "     |  js_on_change(self, event: 'str', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |      Attach a ``CustomJS`` callback to an arbitrary BokehJS model event.\n",
      "     |      \n",
      "     |      On the BokehJS side, change events for model properties have the\n",
      "     |      form ``\"change:property_name\"``. As a convenience, if the event name\n",
      "     |      passed to this method is also the name of a property on the model,\n",
      "     |      then it will be prefixed with ``\"change:\"`` automatically:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          # these two are equivalent\n",
      "     |          source.js_on_change('data', callback)\n",
      "     |          source.js_on_change('change:data', callback)\n",
      "     |      \n",
      "     |      However, there are other kinds of events that can be useful to respond\n",
      "     |      to, in addition to property change events. For example to run a\n",
      "     |      callback whenever data is streamed to a ``ColumnDataSource``, use the\n",
      "     |      ``\"stream\"`` event on the source:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          source.js_on_change('streaming', callback)\n",
      "     |  \n",
      "     |  js_on_event(self, event: 'str | Type[Event]', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |  \n",
      "     |  on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Add a callback on this object to trigger when ``attr`` changes.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          attr (str) : an attribute name on this object\n",
      "     |          *callbacks (callable) : callback functions to register\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          widget.on_change('value', callback1, callback2, ..., callback_n)\n",
      "     |  \n",
      "     |  references(self) -> 'Set[Model]'\n",
      "     |      Returns all ``Models`` that this object has references to.\n",
      "     |  \n",
      "     |  select(self, selector: 'SelectorType') -> 'Iterable[Model]'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          seq[Model]\n",
      "     |  \n",
      "     |  select_one(self, selector: 'SelectorType') -> 'Model | None'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.  Raises an error if more than one object\n",
      "     |      is found.  Returns single matching object, or None if nothing is found\n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          Model\n",
      "     |  \n",
      "     |  set_select(self, selector: 'Type[Model] | SelectorType', updates: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Update objects that match a given selector with the specified\n",
      "     |      attribute/value updates.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |          updates (dict) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  to_json(self, include_defaults: 'bool') -> 'JSON'\n",
      "     |      Returns a dictionary of the attributes of this object,\n",
      "     |      containing only \"JSON types\" (string, number, boolean,\n",
      "     |      none, dict, list).\n",
      "     |      \n",
      "     |      References to other objects are serialized as \"refs\" (just\n",
      "     |      the object ID and type info), so the deserializer will\n",
      "     |      need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  to_json_string(self, include_defaults: 'bool') -> 'str'\n",
      "     |      Returns a JSON string encoding the attributes of this object.\n",
      "     |      \n",
      "     |      References to other objects are serialized as references\n",
      "     |      (just the object ID and type info), so the deserializer\n",
      "     |      will need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json_string()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  trigger(self, attr: 'str', old: 'Unknown', new: 'Unknown', hint: 'DocumentPatchedEvent | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init_subclass__() from bokeh.core.has_props.MetaHasProps\n",
      "     |      This method is called when a class is subclassed.\n",
      "     |      \n",
      "     |      The default implementation does nothing. It may be\n",
      "     |      overridden to extend subclasses.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __new__(cls, *args, **kwargs) -> 'Model'\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  id\n",
      "     |  \n",
      "     |  js_event_callbacks\n",
      "     |      A mapping of event names to lists of ``CustomJS`` callbacks.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_event`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('tap event occurred')\")\n",
      "     |          plot.js_on_event('tap', callback)\n",
      "     |  \n",
      "     |  js_property_callbacks\n",
      "     |      A mapping of attribute names to lists of ``CustomJS`` callbacks, to be set up on\n",
      "     |      BokehJS side when the document is created.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_change`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('stuff')\")\n",
      "     |          plot.x_range.js_on_change('start', callback)\n",
      "     |  \n",
      "     |  name\n",
      "     |      An arbitrary, user-supplied name for this model.\n",
      "     |      \n",
      "     |      This name can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models.\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> plot.circle([1,2,3], [4,5,6], name=\"temp\")\n",
      "     |          >>> plot.select(name=\"temp\")\n",
      "     |          [GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any names\n",
      "     |          that are provided, nor is the name used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ref\n",
      "     |  \n",
      "     |  struct\n",
      "     |      A Bokeh protocol \"structure\" of this model, i.e. a dict of the form:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          {\n",
      "     |              'type' : << view model name >>\n",
      "     |              'id'   : << unique model id >>\n",
      "     |          }\n",
      "     |      \n",
      "     |      Additionally there may be a `subtype` field if this model is a subtype.\n",
      "     |  \n",
      "     |  subscribed_events\n",
      "     |      List of events that are subscribed to by Python callbacks. This is\n",
      "     |      the set of events that will be communicated from BokehJS back to\n",
      "     |      Python for this model.\n",
      "     |  \n",
      "     |  syncable\n",
      "     |      Indicates whether this model should be synchronized back to a Bokeh server when\n",
      "     |      updated in a web browser. Setting to ``False`` may be useful to reduce network\n",
      "     |      traffic when dealing with frequently updated objects whose updated values we\n",
      "     |      don't need.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          Setting this property to ``False`` will prevent any ``on_change()`` callbacks\n",
      "     |          on this object from triggering. However, any JS-side callbacks will still\n",
      "     |          work.\n",
      "     |  \n",
      "     |  tags\n",
      "     |      An optional list of arbitrary, user-supplied values to attach to this\n",
      "     |      model.\n",
      "     |      \n",
      "     |      This data can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> r = plot.circle([1,2,3], [4,5,6])\n",
      "     |          >>> r.tags = [\"foo\", 10]\n",
      "     |          >>> plot.select(tags=['foo', 10])\n",
      "     |          [GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]\n",
      "     |      \n",
      "     |      Or simply a convenient way to attach any necessary metadata to a model\n",
      "     |      that can be accessed by ``CustomJS`` callbacks, etc.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any tags\n",
      "     |          that are provided, nor are the tags used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __annotations__ = {'_id': 'ID', 'model_class_reverse_map': 'ClassVar[D...\n",
      "     |  \n",
      "     |  model_class_reverse_map = {'AbstractButton': <class 'bokeh.models.widg...\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __getattr__(self, name: 'str') -> 'Unknown'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  __setattr__(self, name: 'str', value: 'Unknown') -> 'None'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  apply_theme(self, property_values: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Apply a set of theme values which will be used rather than\n",
      "     |      defaults, but will not override application-set values.\n",
      "     |      \n",
      "     |      The passed-in dictionary may be kept around as-is and shared with\n",
      "     |      other instances to save memory (so neither the caller nor the\n",
      "     |      |HasProps| instance should modify it).\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          property_values (dict) : theme values to use in place of defaults\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  equals(self, other: 'HasProps') -> 'bool'\n",
      "     |      Structural equality of models.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          other (HasProps) : the other instance to compare to\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          True, if properties are structurally equal, otherwise False\n",
      "     |  \n",
      "     |  properties_with_values(self, *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Collect a dict mapping property names to their values.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Non-serializable properties are skipped and property values are in\n",
      "     |      \"serialized\" format which may be slightly different from the values\n",
      "     |      you would normally read from the properties; the intent of this method\n",
      "     |      is to return the information needed to losslessly reconstitute the\n",
      "     |      object instance.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that haven't been explicitly set\n",
      "     |              since the object was created. (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |         dict : mapping from property names to their values\n",
      "     |  \n",
      "     |  query_properties_with_values(self, query: 'Callable[[PropertyDescriptor[Any]], bool]', *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Query the properties values of |HasProps| instances with a\n",
      "     |      predicate.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          query (callable) :\n",
      "     |              A callable that accepts property descriptors and returns True\n",
      "     |              or False\n",
      "     |      \n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that have not been explicitly\n",
      "     |              set by a user (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict : mapping of property names and values for matching properties\n",
      "     |  \n",
      "     |  set_from_json(self, name: 'str', json: 'JSON', *, models: 'Dict[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Set a property value on this object from JSON.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name: (str) : name of the attribute to set\n",
      "     |      \n",
      "     |          json: (JSON-value) : value to set to the attribute to\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  themed_values(self) -> 'Dict[str, Unknown] | None'\n",
      "     |      Get any theme-provided overrides.\n",
      "     |      \n",
      "     |      Results are returned as a dict from property name to value, or\n",
      "     |      ``None`` if no theme overrides any values for this instance.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict or None\n",
      "     |  \n",
      "     |  to_serializable(self, serializer: 'Any') -> 'Any'\n",
      "     |  \n",
      "     |  unapply_theme(self) -> 'None'\n",
      "     |      Remove any themed values and restore defaults.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  update(self, **kwargs: 'Any') -> 'None'\n",
      "     |      Updates the object's properties from the given keyword arguments.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          The following are equivalent:\n",
      "     |      \n",
      "     |          .. code-block:: python\n",
      "     |      \n",
      "     |              from bokeh.models import Range1d\n",
      "     |      \n",
      "     |              r = Range1d\n",
      "     |      \n",
      "     |              # set properties individually:\n",
      "     |              r.start = 10\n",
      "     |              r.end = 20\n",
      "     |      \n",
      "     |              # update properties together:\n",
      "     |              r.update(start=10, end=20)\n",
      "     |  \n",
      "     |  update_from_json(self, json_attributes: 'Dict[str, JSON]', *, models: 'Mapping[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Updates the object's properties from a JSON attributes dictionary.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          json_attributes: (JSON-dict) : attributes and values to update\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  dataspecs() -> 'Dict[str, DataSpec]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all ``DataSpec`` properties on this class.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of ``DataSpec`` properties\n",
      "     |  \n",
      "     |  lookup(name: 'str', *, raises: 'bool' = True) -> 'PropertyDescriptor[Any] | None' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Find the ``PropertyDescriptor`` for a Bokeh property on a class,\n",
      "     |      given the property name.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : name of the property to search for\n",
      "     |          raises (bool) : whether to raise or return None if missing\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          PropertyDescriptor : descriptor for property named ``name``\n",
      "     |  \n",
      "     |  properties(*, _with_props: 'bool' = False) -> 'Union[Set[str], Dict[str, Property[Any]]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of properties on this class.\n",
      "     |      \n",
      "     |      .. warning::\n",
      "     |          In a future version of Bokeh, this method will return a dictionary\n",
      "     |          mapping property names to property objects. To future-proof this\n",
      "     |          current usage of this method, wrap the return value in ``list``.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          property names\n",
      "     |  \n",
      "     |  properties_with_refs() -> 'Dict[str, Property[Any]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all properties on this class that also have\n",
      "     |      references.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of properties that have references\n",
      "     |  \n",
      "     |  static_to_serializable(serializer: 'StaticSerializer') -> 'ModelRef' from bokeh.core.has_props.MetaHasProps\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.util.HasDocumentRef:\n",
      "     |  \n",
      "     |  document\n",
      "     |      The |Document| this model is attached to (can be ``None``)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.PropertyCallbackManager:\n",
      "     |  \n",
      "     |  remove_on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Remove a callback from this object\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.EventCallbackManager:\n",
      "     |  \n",
      "     |  on_event(self, event: 'str | Type[Event]', *callbacks: 'EventCallback') -> 'None'\n",
      "     |      Run callbacks when the specified event occurs on this Model\n",
      "     |      \n",
      "     |      Not all Events are supported for all Models.\n",
      "     |      See specific Events in :ref:`bokeh.events` for more information on\n",
      "     |      which Models are able to trigger them.\n",
      "    \n",
      "    class CustomJSFilter(Filter)\n",
      "     |  CustomJSFilter(*args, **kwargs) -> 'Model'\n",
      "     |  \n",
      "     |  Filter data sources with a custom defined JavaScript function.\n",
      "     |  \n",
      "     |  .. warning::\n",
      "     |      The explicit purpose of this Bokeh Model is to embed *raw JavaScript\n",
      "     |      code* for a browser to execute. If any part of the code is derived\n",
      "     |      from untrusted user inputs, then you must take appropriate care to\n",
      "     |      sanitize the user input prior to passing to Bokeh.\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      CustomJSFilter\n",
      "     |      Filter\n",
      "     |      bokeh.model.model.Model\n",
      "     |      bokeh.core.has_props.HasProps\n",
      "     |      bokeh.model.util.HasDocumentRef\n",
      "     |      bokeh.util.callback_manager.PropertyCallbackManager\n",
      "     |      bokeh.util.callback_manager.EventCallbackManager\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  args\n",
      "     |      A mapping of names to Python objects. In particular those can be bokeh's models.\n",
      "     |      These objects are made available to the callback's code snippet as the values of\n",
      "     |      named parameters to the callback.\n",
      "     |  \n",
      "     |  code\n",
      "     |      A snippet of JavaScript code to filter data contained in a columnar data source.\n",
      "     |      The code is made into the body of a function, and all of of the named objects in\n",
      "     |      ``args`` are available as parameters that the code can use. The variable\n",
      "     |      ``source`` will contain the data source that is associated with the ``CDSView`` this\n",
      "     |      filter is added to.\n",
      "     |      \n",
      "     |      The code should either return the indices of the subset or an array of booleans\n",
      "     |      to use to subset data source rows.\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |          .. code-block\n",
      "     |      \n",
      "     |              code = '''\n",
      "     |              const indices = []\n",
      "     |              for (let i = 0; i <= source.data['some_column'].length; i++) {\n",
      "     |                  if (source.data['some_column'][i] == 'some_value') {\n",
      "     |                      indices.push(i)\n",
      "     |                  }\n",
      "     |              }\n",
      "     |              return indices\n",
      "     |              '''\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __overridden_defaults__ = {}\n",
      "     |  \n",
      "     |  __properties__ = {'args': <bokeh.core.property.container.RestrictedDic...\n",
      "     |  \n",
      "     |  __qualified_model__ = 'CustomJSFilter'\n",
      "     |  \n",
      "     |  __view_model__ = 'CustomJSFilter'\n",
      "     |  \n",
      "     |  __view_module__ = 'bokeh.models.filters'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init__(self, **kwargs: 'Any') -> 'None'\n",
      "     |  \n",
      "     |  __repr__ = __str__(self) -> 'str'\n",
      "     |  \n",
      "     |  __str__(self) -> 'str'\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  destroy(self) -> 'None'\n",
      "     |      Clean up references to the document and property\n",
      "     |  \n",
      "     |  js_link(self, attr: 'str', other: 'Model', other_attr: 'str', attr_selector: 'int | str | None' = None) -> 'None'\n",
      "     |      Link two Bokeh model properties using JavaScript.\n",
      "     |      \n",
      "     |      This is a convenience method that simplifies adding a CustomJS callback\n",
      "     |      to update one Bokeh model property whenever another changes value.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |      \n",
      "     |          attr (str) :\n",
      "     |              The name of a Bokeh property on this model\n",
      "     |      \n",
      "     |          other (Model):\n",
      "     |              A Bokeh model to link to self.attr\n",
      "     |      \n",
      "     |          other_attr (str) :\n",
      "     |              The property on ``other`` to link together\n",
      "     |      \n",
      "     |          attr_selector (Union[int, str]) :\n",
      "     |              The index to link an item in a subscriptable ``attr``\n",
      "     |      \n",
      "     |      Added in version 1.1\n",
      "     |      \n",
      "     |      Raises:\n",
      "     |      \n",
      "     |          ValueError\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          This code with ``js_link``:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              select.js_link('value', plot, 'sizing_mode')\n",
      "     |      \n",
      "     |          is equivalent to the following:\n",
      "     |      \n",
      "     |          .. code:: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              select.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot),\n",
      "     |                           code=\"other.sizing_mode = this.value\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |      \n",
      "     |          Additionally, to use attr_selector to attach the left side of a range slider to a plot's x_range:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)\n",
      "     |      \n",
      "     |          which is equivalent to:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              range_slider.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot.x_range),\n",
      "     |                           code=\"other.start = this.value[0]\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |  \n",
      "     |  js_on_change(self, event: 'str', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |      Attach a ``CustomJS`` callback to an arbitrary BokehJS model event.\n",
      "     |      \n",
      "     |      On the BokehJS side, change events for model properties have the\n",
      "     |      form ``\"change:property_name\"``. As a convenience, if the event name\n",
      "     |      passed to this method is also the name of a property on the model,\n",
      "     |      then it will be prefixed with ``\"change:\"`` automatically:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          # these two are equivalent\n",
      "     |          source.js_on_change('data', callback)\n",
      "     |          source.js_on_change('change:data', callback)\n",
      "     |      \n",
      "     |      However, there are other kinds of events that can be useful to respond\n",
      "     |      to, in addition to property change events. For example to run a\n",
      "     |      callback whenever data is streamed to a ``ColumnDataSource``, use the\n",
      "     |      ``\"stream\"`` event on the source:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          source.js_on_change('streaming', callback)\n",
      "     |  \n",
      "     |  js_on_event(self, event: 'str | Type[Event]', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |  \n",
      "     |  on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Add a callback on this object to trigger when ``attr`` changes.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          attr (str) : an attribute name on this object\n",
      "     |          *callbacks (callable) : callback functions to register\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          widget.on_change('value', callback1, callback2, ..., callback_n)\n",
      "     |  \n",
      "     |  references(self) -> 'Set[Model]'\n",
      "     |      Returns all ``Models`` that this object has references to.\n",
      "     |  \n",
      "     |  select(self, selector: 'SelectorType') -> 'Iterable[Model]'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          seq[Model]\n",
      "     |  \n",
      "     |  select_one(self, selector: 'SelectorType') -> 'Model | None'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.  Raises an error if more than one object\n",
      "     |      is found.  Returns single matching object, or None if nothing is found\n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          Model\n",
      "     |  \n",
      "     |  set_select(self, selector: 'Type[Model] | SelectorType', updates: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Update objects that match a given selector with the specified\n",
      "     |      attribute/value updates.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |          updates (dict) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  to_json(self, include_defaults: 'bool') -> 'JSON'\n",
      "     |      Returns a dictionary of the attributes of this object,\n",
      "     |      containing only \"JSON types\" (string, number, boolean,\n",
      "     |      none, dict, list).\n",
      "     |      \n",
      "     |      References to other objects are serialized as \"refs\" (just\n",
      "     |      the object ID and type info), so the deserializer will\n",
      "     |      need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  to_json_string(self, include_defaults: 'bool') -> 'str'\n",
      "     |      Returns a JSON string encoding the attributes of this object.\n",
      "     |      \n",
      "     |      References to other objects are serialized as references\n",
      "     |      (just the object ID and type info), so the deserializer\n",
      "     |      will need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json_string()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  trigger(self, attr: 'str', old: 'Unknown', new: 'Unknown', hint: 'DocumentPatchedEvent | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init_subclass__() from bokeh.core.has_props.MetaHasProps\n",
      "     |      This method is called when a class is subclassed.\n",
      "     |      \n",
      "     |      The default implementation does nothing. It may be\n",
      "     |      overridden to extend subclasses.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __new__(cls, *args, **kwargs) -> 'Model'\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  id\n",
      "     |  \n",
      "     |  js_event_callbacks\n",
      "     |      A mapping of event names to lists of ``CustomJS`` callbacks.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_event`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('tap event occurred')\")\n",
      "     |          plot.js_on_event('tap', callback)\n",
      "     |  \n",
      "     |  js_property_callbacks\n",
      "     |      A mapping of attribute names to lists of ``CustomJS`` callbacks, to be set up on\n",
      "     |      BokehJS side when the document is created.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_change`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('stuff')\")\n",
      "     |          plot.x_range.js_on_change('start', callback)\n",
      "     |  \n",
      "     |  name\n",
      "     |      An arbitrary, user-supplied name for this model.\n",
      "     |      \n",
      "     |      This name can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models.\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> plot.circle([1,2,3], [4,5,6], name=\"temp\")\n",
      "     |          >>> plot.select(name=\"temp\")\n",
      "     |          [GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any names\n",
      "     |          that are provided, nor is the name used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ref\n",
      "     |  \n",
      "     |  struct\n",
      "     |      A Bokeh protocol \"structure\" of this model, i.e. a dict of the form:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          {\n",
      "     |              'type' : << view model name >>\n",
      "     |              'id'   : << unique model id >>\n",
      "     |          }\n",
      "     |      \n",
      "     |      Additionally there may be a `subtype` field if this model is a subtype.\n",
      "     |  \n",
      "     |  subscribed_events\n",
      "     |      List of events that are subscribed to by Python callbacks. This is\n",
      "     |      the set of events that will be communicated from BokehJS back to\n",
      "     |      Python for this model.\n",
      "     |  \n",
      "     |  syncable\n",
      "     |      Indicates whether this model should be synchronized back to a Bokeh server when\n",
      "     |      updated in a web browser. Setting to ``False`` may be useful to reduce network\n",
      "     |      traffic when dealing with frequently updated objects whose updated values we\n",
      "     |      don't need.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          Setting this property to ``False`` will prevent any ``on_change()`` callbacks\n",
      "     |          on this object from triggering. However, any JS-side callbacks will still\n",
      "     |          work.\n",
      "     |  \n",
      "     |  tags\n",
      "     |      An optional list of arbitrary, user-supplied values to attach to this\n",
      "     |      model.\n",
      "     |      \n",
      "     |      This data can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> r = plot.circle([1,2,3], [4,5,6])\n",
      "     |          >>> r.tags = [\"foo\", 10]\n",
      "     |          >>> plot.select(tags=['foo', 10])\n",
      "     |          [GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]\n",
      "     |      \n",
      "     |      Or simply a convenient way to attach any necessary metadata to a model\n",
      "     |      that can be accessed by ``CustomJS`` callbacks, etc.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any tags\n",
      "     |          that are provided, nor are the tags used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __annotations__ = {'_id': 'ID', 'model_class_reverse_map': 'ClassVar[D...\n",
      "     |  \n",
      "     |  model_class_reverse_map = {'AbstractButton': <class 'bokeh.models.widg...\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __getattr__(self, name: 'str') -> 'Unknown'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  __setattr__(self, name: 'str', value: 'Unknown') -> 'None'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  apply_theme(self, property_values: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Apply a set of theme values which will be used rather than\n",
      "     |      defaults, but will not override application-set values.\n",
      "     |      \n",
      "     |      The passed-in dictionary may be kept around as-is and shared with\n",
      "     |      other instances to save memory (so neither the caller nor the\n",
      "     |      |HasProps| instance should modify it).\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          property_values (dict) : theme values to use in place of defaults\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  equals(self, other: 'HasProps') -> 'bool'\n",
      "     |      Structural equality of models.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          other (HasProps) : the other instance to compare to\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          True, if properties are structurally equal, otherwise False\n",
      "     |  \n",
      "     |  properties_with_values(self, *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Collect a dict mapping property names to their values.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Non-serializable properties are skipped and property values are in\n",
      "     |      \"serialized\" format which may be slightly different from the values\n",
      "     |      you would normally read from the properties; the intent of this method\n",
      "     |      is to return the information needed to losslessly reconstitute the\n",
      "     |      object instance.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that haven't been explicitly set\n",
      "     |              since the object was created. (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |         dict : mapping from property names to their values\n",
      "     |  \n",
      "     |  query_properties_with_values(self, query: 'Callable[[PropertyDescriptor[Any]], bool]', *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Query the properties values of |HasProps| instances with a\n",
      "     |      predicate.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          query (callable) :\n",
      "     |              A callable that accepts property descriptors and returns True\n",
      "     |              or False\n",
      "     |      \n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that have not been explicitly\n",
      "     |              set by a user (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict : mapping of property names and values for matching properties\n",
      "     |  \n",
      "     |  set_from_json(self, name: 'str', json: 'JSON', *, models: 'Dict[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Set a property value on this object from JSON.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name: (str) : name of the attribute to set\n",
      "     |      \n",
      "     |          json: (JSON-value) : value to set to the attribute to\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  themed_values(self) -> 'Dict[str, Unknown] | None'\n",
      "     |      Get any theme-provided overrides.\n",
      "     |      \n",
      "     |      Results are returned as a dict from property name to value, or\n",
      "     |      ``None`` if no theme overrides any values for this instance.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict or None\n",
      "     |  \n",
      "     |  to_serializable(self, serializer: 'Any') -> 'Any'\n",
      "     |  \n",
      "     |  unapply_theme(self) -> 'None'\n",
      "     |      Remove any themed values and restore defaults.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  update(self, **kwargs: 'Any') -> 'None'\n",
      "     |      Updates the object's properties from the given keyword arguments.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          The following are equivalent:\n",
      "     |      \n",
      "     |          .. code-block:: python\n",
      "     |      \n",
      "     |              from bokeh.models import Range1d\n",
      "     |      \n",
      "     |              r = Range1d\n",
      "     |      \n",
      "     |              # set properties individually:\n",
      "     |              r.start = 10\n",
      "     |              r.end = 20\n",
      "     |      \n",
      "     |              # update properties together:\n",
      "     |              r.update(start=10, end=20)\n",
      "     |  \n",
      "     |  update_from_json(self, json_attributes: 'Dict[str, JSON]', *, models: 'Mapping[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Updates the object's properties from a JSON attributes dictionary.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          json_attributes: (JSON-dict) : attributes and values to update\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  dataspecs() -> 'Dict[str, DataSpec]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all ``DataSpec`` properties on this class.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of ``DataSpec`` properties\n",
      "     |  \n",
      "     |  lookup(name: 'str', *, raises: 'bool' = True) -> 'PropertyDescriptor[Any] | None' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Find the ``PropertyDescriptor`` for a Bokeh property on a class,\n",
      "     |      given the property name.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : name of the property to search for\n",
      "     |          raises (bool) : whether to raise or return None if missing\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          PropertyDescriptor : descriptor for property named ``name``\n",
      "     |  \n",
      "     |  properties(*, _with_props: 'bool' = False) -> 'Union[Set[str], Dict[str, Property[Any]]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of properties on this class.\n",
      "     |      \n",
      "     |      .. warning::\n",
      "     |          In a future version of Bokeh, this method will return a dictionary\n",
      "     |          mapping property names to property objects. To future-proof this\n",
      "     |          current usage of this method, wrap the return value in ``list``.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          property names\n",
      "     |  \n",
      "     |  properties_with_refs() -> 'Dict[str, Property[Any]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all properties on this class that also have\n",
      "     |      references.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of properties that have references\n",
      "     |  \n",
      "     |  static_to_serializable(serializer: 'StaticSerializer') -> 'ModelRef' from bokeh.core.has_props.MetaHasProps\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.util.HasDocumentRef:\n",
      "     |  \n",
      "     |  document\n",
      "     |      The |Document| this model is attached to (can be ``None``)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.PropertyCallbackManager:\n",
      "     |  \n",
      "     |  remove_on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Remove a callback from this object\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.EventCallbackManager:\n",
      "     |  \n",
      "     |  on_event(self, event: 'str | Type[Event]', *callbacks: 'EventCallback') -> 'None'\n",
      "     |      Run callbacks when the specified event occurs on this Model\n",
      "     |      \n",
      "     |      Not all Events are supported for all Models.\n",
      "     |      See specific Events in :ref:`bokeh.events` for more information on\n",
      "     |      which Models are able to trigger them.\n",
      "    \n",
      "    class Filter(bokeh.model.model.Model)\n",
      "     |  Filter(*args, **kwargs) -> 'Model'\n",
      "     |  \n",
      "     |  A Filter model represents a filtering operation that returns a row-wise subset of\n",
      "     |  data when applied to a ``ColumnDataSource``.\n",
      "     |  \n",
      "     |  .. note::\n",
      "     |      This is an abstract base class used to help organize the hierarchy of Bokeh\n",
      "     |      model types. **It is not useful to instantiate on its own.**\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      Filter\n",
      "     |      bokeh.model.model.Model\n",
      "     |      bokeh.core.has_props.HasProps\n",
      "     |      bokeh.model.util.HasDocumentRef\n",
      "     |      bokeh.util.callback_manager.PropertyCallbackManager\n",
      "     |      bokeh.util.callback_manager.EventCallbackManager\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __overridden_defaults__ = {}\n",
      "     |  \n",
      "     |  __properties__ = {}\n",
      "     |  \n",
      "     |  __qualified_model__ = 'Filter'\n",
      "     |  \n",
      "     |  __view_model__ = 'Filter'\n",
      "     |  \n",
      "     |  __view_module__ = 'bokeh.models.filters'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init__(self, **kwargs: 'Any') -> 'None'\n",
      "     |  \n",
      "     |  __repr__ = __str__(self) -> 'str'\n",
      "     |  \n",
      "     |  __str__(self) -> 'str'\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  destroy(self) -> 'None'\n",
      "     |      Clean up references to the document and property\n",
      "     |  \n",
      "     |  js_link(self, attr: 'str', other: 'Model', other_attr: 'str', attr_selector: 'int | str | None' = None) -> 'None'\n",
      "     |      Link two Bokeh model properties using JavaScript.\n",
      "     |      \n",
      "     |      This is a convenience method that simplifies adding a CustomJS callback\n",
      "     |      to update one Bokeh model property whenever another changes value.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |      \n",
      "     |          attr (str) :\n",
      "     |              The name of a Bokeh property on this model\n",
      "     |      \n",
      "     |          other (Model):\n",
      "     |              A Bokeh model to link to self.attr\n",
      "     |      \n",
      "     |          other_attr (str) :\n",
      "     |              The property on ``other`` to link together\n",
      "     |      \n",
      "     |          attr_selector (Union[int, str]) :\n",
      "     |              The index to link an item in a subscriptable ``attr``\n",
      "     |      \n",
      "     |      Added in version 1.1\n",
      "     |      \n",
      "     |      Raises:\n",
      "     |      \n",
      "     |          ValueError\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          This code with ``js_link``:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              select.js_link('value', plot, 'sizing_mode')\n",
      "     |      \n",
      "     |          is equivalent to the following:\n",
      "     |      \n",
      "     |          .. code:: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              select.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot),\n",
      "     |                           code=\"other.sizing_mode = this.value\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |      \n",
      "     |          Additionally, to use attr_selector to attach the left side of a range slider to a plot's x_range:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)\n",
      "     |      \n",
      "     |          which is equivalent to:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              range_slider.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot.x_range),\n",
      "     |                           code=\"other.start = this.value[0]\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |  \n",
      "     |  js_on_change(self, event: 'str', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |      Attach a ``CustomJS`` callback to an arbitrary BokehJS model event.\n",
      "     |      \n",
      "     |      On the BokehJS side, change events for model properties have the\n",
      "     |      form ``\"change:property_name\"``. As a convenience, if the event name\n",
      "     |      passed to this method is also the name of a property on the model,\n",
      "     |      then it will be prefixed with ``\"change:\"`` automatically:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          # these two are equivalent\n",
      "     |          source.js_on_change('data', callback)\n",
      "     |          source.js_on_change('change:data', callback)\n",
      "     |      \n",
      "     |      However, there are other kinds of events that can be useful to respond\n",
      "     |      to, in addition to property change events. For example to run a\n",
      "     |      callback whenever data is streamed to a ``ColumnDataSource``, use the\n",
      "     |      ``\"stream\"`` event on the source:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          source.js_on_change('streaming', callback)\n",
      "     |  \n",
      "     |  js_on_event(self, event: 'str | Type[Event]', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |  \n",
      "     |  on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Add a callback on this object to trigger when ``attr`` changes.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          attr (str) : an attribute name on this object\n",
      "     |          *callbacks (callable) : callback functions to register\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          widget.on_change('value', callback1, callback2, ..., callback_n)\n",
      "     |  \n",
      "     |  references(self) -> 'Set[Model]'\n",
      "     |      Returns all ``Models`` that this object has references to.\n",
      "     |  \n",
      "     |  select(self, selector: 'SelectorType') -> 'Iterable[Model]'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          seq[Model]\n",
      "     |  \n",
      "     |  select_one(self, selector: 'SelectorType') -> 'Model | None'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.  Raises an error if more than one object\n",
      "     |      is found.  Returns single matching object, or None if nothing is found\n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          Model\n",
      "     |  \n",
      "     |  set_select(self, selector: 'Type[Model] | SelectorType', updates: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Update objects that match a given selector with the specified\n",
      "     |      attribute/value updates.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |          updates (dict) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  to_json(self, include_defaults: 'bool') -> 'JSON'\n",
      "     |      Returns a dictionary of the attributes of this object,\n",
      "     |      containing only \"JSON types\" (string, number, boolean,\n",
      "     |      none, dict, list).\n",
      "     |      \n",
      "     |      References to other objects are serialized as \"refs\" (just\n",
      "     |      the object ID and type info), so the deserializer will\n",
      "     |      need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  to_json_string(self, include_defaults: 'bool') -> 'str'\n",
      "     |      Returns a JSON string encoding the attributes of this object.\n",
      "     |      \n",
      "     |      References to other objects are serialized as references\n",
      "     |      (just the object ID and type info), so the deserializer\n",
      "     |      will need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json_string()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  trigger(self, attr: 'str', old: 'Unknown', new: 'Unknown', hint: 'DocumentPatchedEvent | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init_subclass__() from bokeh.core.has_props.MetaHasProps\n",
      "     |      This method is called when a class is subclassed.\n",
      "     |      \n",
      "     |      The default implementation does nothing. It may be\n",
      "     |      overridden to extend subclasses.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __new__(cls, *args, **kwargs) -> 'Model'\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  id\n",
      "     |  \n",
      "     |  js_event_callbacks\n",
      "     |      A mapping of event names to lists of ``CustomJS`` callbacks.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_event`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('tap event occurred')\")\n",
      "     |          plot.js_on_event('tap', callback)\n",
      "     |  \n",
      "     |  js_property_callbacks\n",
      "     |      A mapping of attribute names to lists of ``CustomJS`` callbacks, to be set up on\n",
      "     |      BokehJS side when the document is created.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_change`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('stuff')\")\n",
      "     |          plot.x_range.js_on_change('start', callback)\n",
      "     |  \n",
      "     |  name\n",
      "     |      An arbitrary, user-supplied name for this model.\n",
      "     |      \n",
      "     |      This name can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models.\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> plot.circle([1,2,3], [4,5,6], name=\"temp\")\n",
      "     |          >>> plot.select(name=\"temp\")\n",
      "     |          [GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any names\n",
      "     |          that are provided, nor is the name used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ref\n",
      "     |  \n",
      "     |  struct\n",
      "     |      A Bokeh protocol \"structure\" of this model, i.e. a dict of the form:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          {\n",
      "     |              'type' : << view model name >>\n",
      "     |              'id'   : << unique model id >>\n",
      "     |          }\n",
      "     |      \n",
      "     |      Additionally there may be a `subtype` field if this model is a subtype.\n",
      "     |  \n",
      "     |  subscribed_events\n",
      "     |      List of events that are subscribed to by Python callbacks. This is\n",
      "     |      the set of events that will be communicated from BokehJS back to\n",
      "     |      Python for this model.\n",
      "     |  \n",
      "     |  syncable\n",
      "     |      Indicates whether this model should be synchronized back to a Bokeh server when\n",
      "     |      updated in a web browser. Setting to ``False`` may be useful to reduce network\n",
      "     |      traffic when dealing with frequently updated objects whose updated values we\n",
      "     |      don't need.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          Setting this property to ``False`` will prevent any ``on_change()`` callbacks\n",
      "     |          on this object from triggering. However, any JS-side callbacks will still\n",
      "     |          work.\n",
      "     |  \n",
      "     |  tags\n",
      "     |      An optional list of arbitrary, user-supplied values to attach to this\n",
      "     |      model.\n",
      "     |      \n",
      "     |      This data can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> r = plot.circle([1,2,3], [4,5,6])\n",
      "     |          >>> r.tags = [\"foo\", 10]\n",
      "     |          >>> plot.select(tags=['foo', 10])\n",
      "     |          [GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]\n",
      "     |      \n",
      "     |      Or simply a convenient way to attach any necessary metadata to a model\n",
      "     |      that can be accessed by ``CustomJS`` callbacks, etc.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any tags\n",
      "     |          that are provided, nor are the tags used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __annotations__ = {'_id': 'ID', 'model_class_reverse_map': 'ClassVar[D...\n",
      "     |  \n",
      "     |  model_class_reverse_map = {'AbstractButton': <class 'bokeh.models.widg...\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __getattr__(self, name: 'str') -> 'Unknown'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  __setattr__(self, name: 'str', value: 'Unknown') -> 'None'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  apply_theme(self, property_values: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Apply a set of theme values which will be used rather than\n",
      "     |      defaults, but will not override application-set values.\n",
      "     |      \n",
      "     |      The passed-in dictionary may be kept around as-is and shared with\n",
      "     |      other instances to save memory (so neither the caller nor the\n",
      "     |      |HasProps| instance should modify it).\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          property_values (dict) : theme values to use in place of defaults\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  equals(self, other: 'HasProps') -> 'bool'\n",
      "     |      Structural equality of models.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          other (HasProps) : the other instance to compare to\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          True, if properties are structurally equal, otherwise False\n",
      "     |  \n",
      "     |  properties_with_values(self, *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Collect a dict mapping property names to their values.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Non-serializable properties are skipped and property values are in\n",
      "     |      \"serialized\" format which may be slightly different from the values\n",
      "     |      you would normally read from the properties; the intent of this method\n",
      "     |      is to return the information needed to losslessly reconstitute the\n",
      "     |      object instance.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that haven't been explicitly set\n",
      "     |              since the object was created. (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |         dict : mapping from property names to their values\n",
      "     |  \n",
      "     |  query_properties_with_values(self, query: 'Callable[[PropertyDescriptor[Any]], bool]', *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Query the properties values of |HasProps| instances with a\n",
      "     |      predicate.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          query (callable) :\n",
      "     |              A callable that accepts property descriptors and returns True\n",
      "     |              or False\n",
      "     |      \n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that have not been explicitly\n",
      "     |              set by a user (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict : mapping of property names and values for matching properties\n",
      "     |  \n",
      "     |  set_from_json(self, name: 'str', json: 'JSON', *, models: 'Dict[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Set a property value on this object from JSON.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name: (str) : name of the attribute to set\n",
      "     |      \n",
      "     |          json: (JSON-value) : value to set to the attribute to\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  themed_values(self) -> 'Dict[str, Unknown] | None'\n",
      "     |      Get any theme-provided overrides.\n",
      "     |      \n",
      "     |      Results are returned as a dict from property name to value, or\n",
      "     |      ``None`` if no theme overrides any values for this instance.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict or None\n",
      "     |  \n",
      "     |  to_serializable(self, serializer: 'Any') -> 'Any'\n",
      "     |  \n",
      "     |  unapply_theme(self) -> 'None'\n",
      "     |      Remove any themed values and restore defaults.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  update(self, **kwargs: 'Any') -> 'None'\n",
      "     |      Updates the object's properties from the given keyword arguments.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          The following are equivalent:\n",
      "     |      \n",
      "     |          .. code-block:: python\n",
      "     |      \n",
      "     |              from bokeh.models import Range1d\n",
      "     |      \n",
      "     |              r = Range1d\n",
      "     |      \n",
      "     |              # set properties individually:\n",
      "     |              r.start = 10\n",
      "     |              r.end = 20\n",
      "     |      \n",
      "     |              # update properties together:\n",
      "     |              r.update(start=10, end=20)\n",
      "     |  \n",
      "     |  update_from_json(self, json_attributes: 'Dict[str, JSON]', *, models: 'Mapping[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Updates the object's properties from a JSON attributes dictionary.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          json_attributes: (JSON-dict) : attributes and values to update\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  dataspecs() -> 'Dict[str, DataSpec]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all ``DataSpec`` properties on this class.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of ``DataSpec`` properties\n",
      "     |  \n",
      "     |  lookup(name: 'str', *, raises: 'bool' = True) -> 'PropertyDescriptor[Any] | None' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Find the ``PropertyDescriptor`` for a Bokeh property on a class,\n",
      "     |      given the property name.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : name of the property to search for\n",
      "     |          raises (bool) : whether to raise or return None if missing\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          PropertyDescriptor : descriptor for property named ``name``\n",
      "     |  \n",
      "     |  properties(*, _with_props: 'bool' = False) -> 'Union[Set[str], Dict[str, Property[Any]]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of properties on this class.\n",
      "     |      \n",
      "     |      .. warning::\n",
      "     |          In a future version of Bokeh, this method will return a dictionary\n",
      "     |          mapping property names to property objects. To future-proof this\n",
      "     |          current usage of this method, wrap the return value in ``list``.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          property names\n",
      "     |  \n",
      "     |  properties_with_refs() -> 'Dict[str, Property[Any]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all properties on this class that also have\n",
      "     |      references.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of properties that have references\n",
      "     |  \n",
      "     |  static_to_serializable(serializer: 'StaticSerializer') -> 'ModelRef' from bokeh.core.has_props.MetaHasProps\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.util.HasDocumentRef:\n",
      "     |  \n",
      "     |  document\n",
      "     |      The |Document| this model is attached to (can be ``None``)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.PropertyCallbackManager:\n",
      "     |  \n",
      "     |  remove_on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Remove a callback from this object\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.EventCallbackManager:\n",
      "     |  \n",
      "     |  on_event(self, event: 'str | Type[Event]', *callbacks: 'EventCallback') -> 'None'\n",
      "     |      Run callbacks when the specified event occurs on this Model\n",
      "     |      \n",
      "     |      Not all Events are supported for all Models.\n",
      "     |      See specific Events in :ref:`bokeh.events` for more information on\n",
      "     |      which Models are able to trigger them.\n",
      "    \n",
      "    class GroupFilter(Filter)\n",
      "     |  GroupFilter(*args, **kwargs) -> 'Model'\n",
      "     |  \n",
      "     |  A ``GroupFilter`` represents the rows of a ``ColumnDataSource`` where the values of the categorical\n",
      "     |  column column_name match the group variable.\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      GroupFilter\n",
      "     |      Filter\n",
      "     |      bokeh.model.model.Model\n",
      "     |      bokeh.core.has_props.HasProps\n",
      "     |      bokeh.model.util.HasDocumentRef\n",
      "     |      bokeh.util.callback_manager.PropertyCallbackManager\n",
      "     |      bokeh.util.callback_manager.EventCallbackManager\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __init__(self, *args, **kw) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  column_name\n",
      "     |      The name of the column to perform the group filtering operation on.\n",
      "     |  \n",
      "     |  group\n",
      "     |      The value of the column indicating the rows of data to keep.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __overridden_defaults__ = {}\n",
      "     |  \n",
      "     |  __properties__ = {'column_name': <bokeh.core.property.nullable.NonNull...\n",
      "     |  \n",
      "     |  __qualified_model__ = 'GroupFilter'\n",
      "     |  \n",
      "     |  __view_model__ = 'GroupFilter'\n",
      "     |  \n",
      "     |  __view_module__ = 'bokeh.models.filters'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __repr__ = __str__(self) -> 'str'\n",
      "     |  \n",
      "     |  __str__(self) -> 'str'\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  destroy(self) -> 'None'\n",
      "     |      Clean up references to the document and property\n",
      "     |  \n",
      "     |  js_link(self, attr: 'str', other: 'Model', other_attr: 'str', attr_selector: 'int | str | None' = None) -> 'None'\n",
      "     |      Link two Bokeh model properties using JavaScript.\n",
      "     |      \n",
      "     |      This is a convenience method that simplifies adding a CustomJS callback\n",
      "     |      to update one Bokeh model property whenever another changes value.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |      \n",
      "     |          attr (str) :\n",
      "     |              The name of a Bokeh property on this model\n",
      "     |      \n",
      "     |          other (Model):\n",
      "     |              A Bokeh model to link to self.attr\n",
      "     |      \n",
      "     |          other_attr (str) :\n",
      "     |              The property on ``other`` to link together\n",
      "     |      \n",
      "     |          attr_selector (Union[int, str]) :\n",
      "     |              The index to link an item in a subscriptable ``attr``\n",
      "     |      \n",
      "     |      Added in version 1.1\n",
      "     |      \n",
      "     |      Raises:\n",
      "     |      \n",
      "     |          ValueError\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          This code with ``js_link``:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              select.js_link('value', plot, 'sizing_mode')\n",
      "     |      \n",
      "     |          is equivalent to the following:\n",
      "     |      \n",
      "     |          .. code:: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              select.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot),\n",
      "     |                           code=\"other.sizing_mode = this.value\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |      \n",
      "     |          Additionally, to use attr_selector to attach the left side of a range slider to a plot's x_range:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)\n",
      "     |      \n",
      "     |          which is equivalent to:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              range_slider.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot.x_range),\n",
      "     |                           code=\"other.start = this.value[0]\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |  \n",
      "     |  js_on_change(self, event: 'str', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |      Attach a ``CustomJS`` callback to an arbitrary BokehJS model event.\n",
      "     |      \n",
      "     |      On the BokehJS side, change events for model properties have the\n",
      "     |      form ``\"change:property_name\"``. As a convenience, if the event name\n",
      "     |      passed to this method is also the name of a property on the model,\n",
      "     |      then it will be prefixed with ``\"change:\"`` automatically:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          # these two are equivalent\n",
      "     |          source.js_on_change('data', callback)\n",
      "     |          source.js_on_change('change:data', callback)\n",
      "     |      \n",
      "     |      However, there are other kinds of events that can be useful to respond\n",
      "     |      to, in addition to property change events. For example to run a\n",
      "     |      callback whenever data is streamed to a ``ColumnDataSource``, use the\n",
      "     |      ``\"stream\"`` event on the source:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          source.js_on_change('streaming', callback)\n",
      "     |  \n",
      "     |  js_on_event(self, event: 'str | Type[Event]', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |  \n",
      "     |  on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Add a callback on this object to trigger when ``attr`` changes.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          attr (str) : an attribute name on this object\n",
      "     |          *callbacks (callable) : callback functions to register\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          widget.on_change('value', callback1, callback2, ..., callback_n)\n",
      "     |  \n",
      "     |  references(self) -> 'Set[Model]'\n",
      "     |      Returns all ``Models`` that this object has references to.\n",
      "     |  \n",
      "     |  select(self, selector: 'SelectorType') -> 'Iterable[Model]'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          seq[Model]\n",
      "     |  \n",
      "     |  select_one(self, selector: 'SelectorType') -> 'Model | None'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.  Raises an error if more than one object\n",
      "     |      is found.  Returns single matching object, or None if nothing is found\n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          Model\n",
      "     |  \n",
      "     |  set_select(self, selector: 'Type[Model] | SelectorType', updates: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Update objects that match a given selector with the specified\n",
      "     |      attribute/value updates.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |          updates (dict) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  to_json(self, include_defaults: 'bool') -> 'JSON'\n",
      "     |      Returns a dictionary of the attributes of this object,\n",
      "     |      containing only \"JSON types\" (string, number, boolean,\n",
      "     |      none, dict, list).\n",
      "     |      \n",
      "     |      References to other objects are serialized as \"refs\" (just\n",
      "     |      the object ID and type info), so the deserializer will\n",
      "     |      need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  to_json_string(self, include_defaults: 'bool') -> 'str'\n",
      "     |      Returns a JSON string encoding the attributes of this object.\n",
      "     |      \n",
      "     |      References to other objects are serialized as references\n",
      "     |      (just the object ID and type info), so the deserializer\n",
      "     |      will need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json_string()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  trigger(self, attr: 'str', old: 'Unknown', new: 'Unknown', hint: 'DocumentPatchedEvent | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init_subclass__() from bokeh.core.has_props.MetaHasProps\n",
      "     |      This method is called when a class is subclassed.\n",
      "     |      \n",
      "     |      The default implementation does nothing. It may be\n",
      "     |      overridden to extend subclasses.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __new__(cls, *args, **kwargs) -> 'Model'\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  id\n",
      "     |  \n",
      "     |  js_event_callbacks\n",
      "     |      A mapping of event names to lists of ``CustomJS`` callbacks.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_event`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('tap event occurred')\")\n",
      "     |          plot.js_on_event('tap', callback)\n",
      "     |  \n",
      "     |  js_property_callbacks\n",
      "     |      A mapping of attribute names to lists of ``CustomJS`` callbacks, to be set up on\n",
      "     |      BokehJS side when the document is created.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_change`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('stuff')\")\n",
      "     |          plot.x_range.js_on_change('start', callback)\n",
      "     |  \n",
      "     |  name\n",
      "     |      An arbitrary, user-supplied name for this model.\n",
      "     |      \n",
      "     |      This name can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models.\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> plot.circle([1,2,3], [4,5,6], name=\"temp\")\n",
      "     |          >>> plot.select(name=\"temp\")\n",
      "     |          [GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any names\n",
      "     |          that are provided, nor is the name used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ref\n",
      "     |  \n",
      "     |  struct\n",
      "     |      A Bokeh protocol \"structure\" of this model, i.e. a dict of the form:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          {\n",
      "     |              'type' : << view model name >>\n",
      "     |              'id'   : << unique model id >>\n",
      "     |          }\n",
      "     |      \n",
      "     |      Additionally there may be a `subtype` field if this model is a subtype.\n",
      "     |  \n",
      "     |  subscribed_events\n",
      "     |      List of events that are subscribed to by Python callbacks. This is\n",
      "     |      the set of events that will be communicated from BokehJS back to\n",
      "     |      Python for this model.\n",
      "     |  \n",
      "     |  syncable\n",
      "     |      Indicates whether this model should be synchronized back to a Bokeh server when\n",
      "     |      updated in a web browser. Setting to ``False`` may be useful to reduce network\n",
      "     |      traffic when dealing with frequently updated objects whose updated values we\n",
      "     |      don't need.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          Setting this property to ``False`` will prevent any ``on_change()`` callbacks\n",
      "     |          on this object from triggering. However, any JS-side callbacks will still\n",
      "     |          work.\n",
      "     |  \n",
      "     |  tags\n",
      "     |      An optional list of arbitrary, user-supplied values to attach to this\n",
      "     |      model.\n",
      "     |      \n",
      "     |      This data can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> r = plot.circle([1,2,3], [4,5,6])\n",
      "     |          >>> r.tags = [\"foo\", 10]\n",
      "     |          >>> plot.select(tags=['foo', 10])\n",
      "     |          [GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]\n",
      "     |      \n",
      "     |      Or simply a convenient way to attach any necessary metadata to a model\n",
      "     |      that can be accessed by ``CustomJS`` callbacks, etc.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any tags\n",
      "     |          that are provided, nor are the tags used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __annotations__ = {'_id': 'ID', 'model_class_reverse_map': 'ClassVar[D...\n",
      "     |  \n",
      "     |  model_class_reverse_map = {'AbstractButton': <class 'bokeh.models.widg...\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __getattr__(self, name: 'str') -> 'Unknown'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  __setattr__(self, name: 'str', value: 'Unknown') -> 'None'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  apply_theme(self, property_values: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Apply a set of theme values which will be used rather than\n",
      "     |      defaults, but will not override application-set values.\n",
      "     |      \n",
      "     |      The passed-in dictionary may be kept around as-is and shared with\n",
      "     |      other instances to save memory (so neither the caller nor the\n",
      "     |      |HasProps| instance should modify it).\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          property_values (dict) : theme values to use in place of defaults\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  equals(self, other: 'HasProps') -> 'bool'\n",
      "     |      Structural equality of models.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          other (HasProps) : the other instance to compare to\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          True, if properties are structurally equal, otherwise False\n",
      "     |  \n",
      "     |  properties_with_values(self, *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Collect a dict mapping property names to their values.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Non-serializable properties are skipped and property values are in\n",
      "     |      \"serialized\" format which may be slightly different from the values\n",
      "     |      you would normally read from the properties; the intent of this method\n",
      "     |      is to return the information needed to losslessly reconstitute the\n",
      "     |      object instance.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that haven't been explicitly set\n",
      "     |              since the object was created. (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |         dict : mapping from property names to their values\n",
      "     |  \n",
      "     |  query_properties_with_values(self, query: 'Callable[[PropertyDescriptor[Any]], bool]', *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Query the properties values of |HasProps| instances with a\n",
      "     |      predicate.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          query (callable) :\n",
      "     |              A callable that accepts property descriptors and returns True\n",
      "     |              or False\n",
      "     |      \n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that have not been explicitly\n",
      "     |              set by a user (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict : mapping of property names and values for matching properties\n",
      "     |  \n",
      "     |  set_from_json(self, name: 'str', json: 'JSON', *, models: 'Dict[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Set a property value on this object from JSON.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name: (str) : name of the attribute to set\n",
      "     |      \n",
      "     |          json: (JSON-value) : value to set to the attribute to\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  themed_values(self) -> 'Dict[str, Unknown] | None'\n",
      "     |      Get any theme-provided overrides.\n",
      "     |      \n",
      "     |      Results are returned as a dict from property name to value, or\n",
      "     |      ``None`` if no theme overrides any values for this instance.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict or None\n",
      "     |  \n",
      "     |  to_serializable(self, serializer: 'Any') -> 'Any'\n",
      "     |  \n",
      "     |  unapply_theme(self) -> 'None'\n",
      "     |      Remove any themed values and restore defaults.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  update(self, **kwargs: 'Any') -> 'None'\n",
      "     |      Updates the object's properties from the given keyword arguments.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          The following are equivalent:\n",
      "     |      \n",
      "     |          .. code-block:: python\n",
      "     |      \n",
      "     |              from bokeh.models import Range1d\n",
      "     |      \n",
      "     |              r = Range1d\n",
      "     |      \n",
      "     |              # set properties individually:\n",
      "     |              r.start = 10\n",
      "     |              r.end = 20\n",
      "     |      \n",
      "     |              # update properties together:\n",
      "     |              r.update(start=10, end=20)\n",
      "     |  \n",
      "     |  update_from_json(self, json_attributes: 'Dict[str, JSON]', *, models: 'Mapping[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Updates the object's properties from a JSON attributes dictionary.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          json_attributes: (JSON-dict) : attributes and values to update\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  dataspecs() -> 'Dict[str, DataSpec]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all ``DataSpec`` properties on this class.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of ``DataSpec`` properties\n",
      "     |  \n",
      "     |  lookup(name: 'str', *, raises: 'bool' = True) -> 'PropertyDescriptor[Any] | None' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Find the ``PropertyDescriptor`` for a Bokeh property on a class,\n",
      "     |      given the property name.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : name of the property to search for\n",
      "     |          raises (bool) : whether to raise or return None if missing\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          PropertyDescriptor : descriptor for property named ``name``\n",
      "     |  \n",
      "     |  properties(*, _with_props: 'bool' = False) -> 'Union[Set[str], Dict[str, Property[Any]]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of properties on this class.\n",
      "     |      \n",
      "     |      .. warning::\n",
      "     |          In a future version of Bokeh, this method will return a dictionary\n",
      "     |          mapping property names to property objects. To future-proof this\n",
      "     |          current usage of this method, wrap the return value in ``list``.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          property names\n",
      "     |  \n",
      "     |  properties_with_refs() -> 'Dict[str, Property[Any]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all properties on this class that also have\n",
      "     |      references.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of properties that have references\n",
      "     |  \n",
      "     |  static_to_serializable(serializer: 'StaticSerializer') -> 'ModelRef' from bokeh.core.has_props.MetaHasProps\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.util.HasDocumentRef:\n",
      "     |  \n",
      "     |  document\n",
      "     |      The |Document| this model is attached to (can be ``None``)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.PropertyCallbackManager:\n",
      "     |  \n",
      "     |  remove_on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Remove a callback from this object\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.EventCallbackManager:\n",
      "     |  \n",
      "     |  on_event(self, event: 'str | Type[Event]', *callbacks: 'EventCallback') -> 'None'\n",
      "     |      Run callbacks when the specified event occurs on this Model\n",
      "     |      \n",
      "     |      Not all Events are supported for all Models.\n",
      "     |      See specific Events in :ref:`bokeh.events` for more information on\n",
      "     |      which Models are able to trigger them.\n",
      "    \n",
      "    class IndexFilter(Filter)\n",
      "     |  IndexFilter(*args, **kwargs) -> 'Model'\n",
      "     |  \n",
      "     |  An ``IndexFilter`` filters data by returning the subset of data at a given set of indices.\n",
      "     |  \n",
      "     |  Method resolution order:\n",
      "     |      IndexFilter\n",
      "     |      Filter\n",
      "     |      bokeh.model.model.Model\n",
      "     |      bokeh.core.has_props.HasProps\n",
      "     |      bokeh.model.util.HasDocumentRef\n",
      "     |      bokeh.util.callback_manager.PropertyCallbackManager\n",
      "     |      bokeh.util.callback_manager.EventCallbackManager\n",
      "     |      builtins.object\n",
      "     |  \n",
      "     |  Methods defined here:\n",
      "     |  \n",
      "     |  __init__(self, *args, **kw) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors defined here:\n",
      "     |  \n",
      "     |  indices\n",
      "     |      A list of integer indices representing the subset of data to select.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes defined here:\n",
      "     |  \n",
      "     |  __overridden_defaults__ = {}\n",
      "     |  \n",
      "     |  __properties__ = {'indices': <bokeh.core.property.nullable.Nullable ob...\n",
      "     |  \n",
      "     |  __qualified_model__ = 'IndexFilter'\n",
      "     |  \n",
      "     |  __view_model__ = 'IndexFilter'\n",
      "     |  \n",
      "     |  __view_module__ = 'bokeh.models.filters'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __repr__ = __str__(self) -> 'str'\n",
      "     |  \n",
      "     |  __str__(self) -> 'str'\n",
      "     |      Return str(self).\n",
      "     |  \n",
      "     |  destroy(self) -> 'None'\n",
      "     |      Clean up references to the document and property\n",
      "     |  \n",
      "     |  js_link(self, attr: 'str', other: 'Model', other_attr: 'str', attr_selector: 'int | str | None' = None) -> 'None'\n",
      "     |      Link two Bokeh model properties using JavaScript.\n",
      "     |      \n",
      "     |      This is a convenience method that simplifies adding a CustomJS callback\n",
      "     |      to update one Bokeh model property whenever another changes value.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |      \n",
      "     |          attr (str) :\n",
      "     |              The name of a Bokeh property on this model\n",
      "     |      \n",
      "     |          other (Model):\n",
      "     |              A Bokeh model to link to self.attr\n",
      "     |      \n",
      "     |          other_attr (str) :\n",
      "     |              The property on ``other`` to link together\n",
      "     |      \n",
      "     |          attr_selector (Union[int, str]) :\n",
      "     |              The index to link an item in a subscriptable ``attr``\n",
      "     |      \n",
      "     |      Added in version 1.1\n",
      "     |      \n",
      "     |      Raises:\n",
      "     |      \n",
      "     |          ValueError\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          This code with ``js_link``:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              select.js_link('value', plot, 'sizing_mode')\n",
      "     |      \n",
      "     |          is equivalent to the following:\n",
      "     |      \n",
      "     |          .. code:: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              select.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot),\n",
      "     |                           code=\"other.sizing_mode = this.value\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |      \n",
      "     |          Additionally, to use attr_selector to attach the left side of a range slider to a plot's x_range:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              range_slider.js_link('value', plot.x_range, 'start', attr_selector=0)\n",
      "     |      \n",
      "     |          which is equivalent to:\n",
      "     |      \n",
      "     |          .. code :: python\n",
      "     |      \n",
      "     |              from bokeh.models import CustomJS\n",
      "     |              range_slider.js_on_change('value',\n",
      "     |                  CustomJS(args=dict(other=plot.x_range),\n",
      "     |                           code=\"other.start = this.value[0]\"\n",
      "     |                  )\n",
      "     |              )\n",
      "     |  \n",
      "     |  js_on_change(self, event: 'str', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |      Attach a ``CustomJS`` callback to an arbitrary BokehJS model event.\n",
      "     |      \n",
      "     |      On the BokehJS side, change events for model properties have the\n",
      "     |      form ``\"change:property_name\"``. As a convenience, if the event name\n",
      "     |      passed to this method is also the name of a property on the model,\n",
      "     |      then it will be prefixed with ``\"change:\"`` automatically:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          # these two are equivalent\n",
      "     |          source.js_on_change('data', callback)\n",
      "     |          source.js_on_change('change:data', callback)\n",
      "     |      \n",
      "     |      However, there are other kinds of events that can be useful to respond\n",
      "     |      to, in addition to property change events. For example to run a\n",
      "     |      callback whenever data is streamed to a ``ColumnDataSource``, use the\n",
      "     |      ``\"stream\"`` event on the source:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          source.js_on_change('streaming', callback)\n",
      "     |  \n",
      "     |  js_on_event(self, event: 'str | Type[Event]', *callbacks: 'JSEventCallback') -> 'None'\n",
      "     |  \n",
      "     |  on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Add a callback on this object to trigger when ``attr`` changes.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          attr (str) : an attribute name on this object\n",
      "     |          *callbacks (callable) : callback functions to register\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Example:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          widget.on_change('value', callback1, callback2, ..., callback_n)\n",
      "     |  \n",
      "     |  references(self) -> 'Set[Model]'\n",
      "     |      Returns all ``Models`` that this object has references to.\n",
      "     |  \n",
      "     |  select(self, selector: 'SelectorType') -> 'Iterable[Model]'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          seq[Model]\n",
      "     |  \n",
      "     |  select_one(self, selector: 'SelectorType') -> 'Model | None'\n",
      "     |      Query this object and all of its references for objects that\n",
      "     |      match the given selector.  Raises an error if more than one object\n",
      "     |      is found.  Returns single matching object, or None if nothing is found\n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          Model\n",
      "     |  \n",
      "     |  set_select(self, selector: 'Type[Model] | SelectorType', updates: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Update objects that match a given selector with the specified\n",
      "     |      attribute/value updates.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          selector (JSON-like) :\n",
      "     |          updates (dict) :\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  to_json(self, include_defaults: 'bool') -> 'JSON'\n",
      "     |      Returns a dictionary of the attributes of this object,\n",
      "     |      containing only \"JSON types\" (string, number, boolean,\n",
      "     |      none, dict, list).\n",
      "     |      \n",
      "     |      References to other objects are serialized as \"refs\" (just\n",
      "     |      the object ID and type info), so the deserializer will\n",
      "     |      need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  to_json_string(self, include_defaults: 'bool') -> 'str'\n",
      "     |      Returns a JSON string encoding the attributes of this object.\n",
      "     |      \n",
      "     |      References to other objects are serialized as references\n",
      "     |      (just the object ID and type info), so the deserializer\n",
      "     |      will need to separately have the full attributes of those\n",
      "     |      other objects.\n",
      "     |      \n",
      "     |      There's no corresponding ``from_json_string()`` because to\n",
      "     |      deserialize an object is normally done in the context of a\n",
      "     |      Document (since the Document can resolve references).\n",
      "     |      \n",
      "     |      For most purposes it's best to serialize and deserialize\n",
      "     |      entire documents.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool) : whether to include attributes\n",
      "     |              that haven't been changed from the default\n",
      "     |  \n",
      "     |  trigger(self, attr: 'str', old: 'Unknown', new: 'Unknown', hint: 'DocumentPatchedEvent | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __init_subclass__() from bokeh.core.has_props.MetaHasProps\n",
      "     |      This method is called when a class is subclassed.\n",
      "     |      \n",
      "     |      The default implementation does nothing. It may be\n",
      "     |      overridden to extend subclasses.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Static methods inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __new__(cls, *args, **kwargs) -> 'Model'\n",
      "     |      Create and return a new object.  See help(type) for accurate signature.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  id\n",
      "     |  \n",
      "     |  js_event_callbacks\n",
      "     |      A mapping of event names to lists of ``CustomJS`` callbacks.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_event`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('tap event occurred')\")\n",
      "     |          plot.js_on_event('tap', callback)\n",
      "     |  \n",
      "     |  js_property_callbacks\n",
      "     |      A mapping of attribute names to lists of ``CustomJS`` callbacks, to be set up on\n",
      "     |      BokehJS side when the document is created.\n",
      "     |      \n",
      "     |      Typically, rather then modifying this property directly, callbacks should be\n",
      "     |      added using the ``Model.js_on_change`` method:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          callback = CustomJS(code=\"console.log('stuff')\")\n",
      "     |          plot.x_range.js_on_change('start', callback)\n",
      "     |  \n",
      "     |  name\n",
      "     |      An arbitrary, user-supplied name for this model.\n",
      "     |      \n",
      "     |      This name can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models.\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> plot.circle([1,2,3], [4,5,6], name=\"temp\")\n",
      "     |          >>> plot.select(name=\"temp\")\n",
      "     |          [GlyphRenderer(id='399d53f5-73e9-44d9-9527-544b761c7705', ...)]\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any names\n",
      "     |          that are provided, nor is the name used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ref\n",
      "     |  \n",
      "     |  struct\n",
      "     |      A Bokeh protocol \"structure\" of this model, i.e. a dict of the form:\n",
      "     |      \n",
      "     |      .. code-block:: python\n",
      "     |      \n",
      "     |          {\n",
      "     |              'type' : << view model name >>\n",
      "     |              'id'   : << unique model id >>\n",
      "     |          }\n",
      "     |      \n",
      "     |      Additionally there may be a `subtype` field if this model is a subtype.\n",
      "     |  \n",
      "     |  subscribed_events\n",
      "     |      List of events that are subscribed to by Python callbacks. This is\n",
      "     |      the set of events that will be communicated from BokehJS back to\n",
      "     |      Python for this model.\n",
      "     |  \n",
      "     |  syncable\n",
      "     |      Indicates whether this model should be synchronized back to a Bokeh server when\n",
      "     |      updated in a web browser. Setting to ``False`` may be useful to reduce network\n",
      "     |      traffic when dealing with frequently updated objects whose updated values we\n",
      "     |      don't need.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          Setting this property to ``False`` will prevent any ``on_change()`` callbacks\n",
      "     |          on this object from triggering. However, any JS-side callbacks will still\n",
      "     |          work.\n",
      "     |  \n",
      "     |  tags\n",
      "     |      An optional list of arbitrary, user-supplied values to attach to this\n",
      "     |      model.\n",
      "     |      \n",
      "     |      This data can be useful when querying the document to retrieve specific\n",
      "     |      Bokeh models:\n",
      "     |      \n",
      "     |      .. code:: python\n",
      "     |      \n",
      "     |          >>> r = plot.circle([1,2,3], [4,5,6])\n",
      "     |          >>> r.tags = [\"foo\", 10]\n",
      "     |          >>> plot.select(tags=['foo', 10])\n",
      "     |          [GlyphRenderer(id='1de4c3df-a83d-480a-899b-fb263d3d5dd9', ...)]\n",
      "     |      \n",
      "     |      Or simply a convenient way to attach any necessary metadata to a model\n",
      "     |      that can be accessed by ``CustomJS`` callbacks, etc.\n",
      "     |      \n",
      "     |      .. note::\n",
      "     |          No uniqueness guarantees or other conditions are enforced on any tags\n",
      "     |          that are provided, nor are the tags used directly by Bokeh for any\n",
      "     |          reason.\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data and other attributes inherited from bokeh.model.model.Model:\n",
      "     |  \n",
      "     |  __annotations__ = {'_id': 'ID', 'model_class_reverse_map': 'ClassVar[D...\n",
      "     |  \n",
      "     |  model_class_reverse_map = {'AbstractButton': <class 'bokeh.models.widg...\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __getattr__(self, name: 'str') -> 'Unknown'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  __setattr__(self, name: 'str', value: 'Unknown') -> 'None'\n",
      "     |      Intercept attribute setting on HasProps in order to special case\n",
      "     |      a few situations:\n",
      "     |      \n",
      "     |      * short circuit all property machinery for ``_private`` attributes\n",
      "     |      * suggest similar attribute names on attribute errors\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : the name of the attribute to set on this object\n",
      "     |          value (obj) : the value to set\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  apply_theme(self, property_values: 'Dict[str, Unknown]') -> 'None'\n",
      "     |      Apply a set of theme values which will be used rather than\n",
      "     |      defaults, but will not override application-set values.\n",
      "     |      \n",
      "     |      The passed-in dictionary may be kept around as-is and shared with\n",
      "     |      other instances to save memory (so neither the caller nor the\n",
      "     |      |HasProps| instance should modify it).\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          property_values (dict) : theme values to use in place of defaults\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  equals(self, other: 'HasProps') -> 'bool'\n",
      "     |      Structural equality of models.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          other (HasProps) : the other instance to compare to\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          True, if properties are structurally equal, otherwise False\n",
      "     |  \n",
      "     |  properties_with_values(self, *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Collect a dict mapping property names to their values.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Non-serializable properties are skipped and property values are in\n",
      "     |      \"serialized\" format which may be slightly different from the values\n",
      "     |      you would normally read from the properties; the intent of this method\n",
      "     |      is to return the information needed to losslessly reconstitute the\n",
      "     |      object instance.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that haven't been explicitly set\n",
      "     |              since the object was created. (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |         dict : mapping from property names to their values\n",
      "     |  \n",
      "     |  query_properties_with_values(self, query: 'Callable[[PropertyDescriptor[Any]], bool]', *, include_defaults: 'bool' = True, include_undefined: 'bool' = False) -> 'Dict[str, Unknown]'\n",
      "     |      Query the properties values of |HasProps| instances with a\n",
      "     |      predicate.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          query (callable) :\n",
      "     |              A callable that accepts property descriptors and returns True\n",
      "     |              or False\n",
      "     |      \n",
      "     |          include_defaults (bool, optional) :\n",
      "     |              Whether to include properties that have not been explicitly\n",
      "     |              set by a user (default: True)\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict : mapping of property names and values for matching properties\n",
      "     |  \n",
      "     |  set_from_json(self, name: 'str', json: 'JSON', *, models: 'Dict[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Set a property value on this object from JSON.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name: (str) : name of the attribute to set\n",
      "     |      \n",
      "     |          json: (JSON-value) : value to set to the attribute to\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  themed_values(self) -> 'Dict[str, Unknown] | None'\n",
      "     |      Get any theme-provided overrides.\n",
      "     |      \n",
      "     |      Results are returned as a dict from property name to value, or\n",
      "     |      ``None`` if no theme overrides any values for this instance.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          dict or None\n",
      "     |  \n",
      "     |  to_serializable(self, serializer: 'Any') -> 'Any'\n",
      "     |  \n",
      "     |  unapply_theme(self) -> 'None'\n",
      "     |      Remove any themed values and restore defaults.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  update(self, **kwargs: 'Any') -> 'None'\n",
      "     |      Updates the object's properties from the given keyword arguments.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |      \n",
      "     |      Examples:\n",
      "     |      \n",
      "     |          The following are equivalent:\n",
      "     |      \n",
      "     |          .. code-block:: python\n",
      "     |      \n",
      "     |              from bokeh.models import Range1d\n",
      "     |      \n",
      "     |              r = Range1d\n",
      "     |      \n",
      "     |              # set properties individually:\n",
      "     |              r.start = 10\n",
      "     |              r.end = 20\n",
      "     |      \n",
      "     |              # update properties together:\n",
      "     |              r.update(start=10, end=20)\n",
      "     |  \n",
      "     |  update_from_json(self, json_attributes: 'Dict[str, JSON]', *, models: 'Mapping[ID, HasProps] | None' = None, setter: 'Setter | None' = None) -> 'None'\n",
      "     |      Updates the object's properties from a JSON attributes dictionary.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          json_attributes: (JSON-dict) : attributes and values to update\n",
      "     |      \n",
      "     |          models (dict or None, optional) :\n",
      "     |              Mapping of model ids to models (default: None)\n",
      "     |      \n",
      "     |              This is needed in cases where the attributes to update also\n",
      "     |              have values that have references.\n",
      "     |      \n",
      "     |          setter(ClientSession or ServerSession or None, optional) :\n",
      "     |              This is used to prevent \"boomerang\" updates to Bokeh apps.\n",
      "     |      \n",
      "     |              In the context of a Bokeh server application, incoming updates\n",
      "     |              to properties will be annotated with the session that is\n",
      "     |              doing the updating. This value is propagated through any\n",
      "     |              subsequent change notifications that the update triggers.\n",
      "     |              The session can compare the event setter to itself, and\n",
      "     |              suppress any updates that originate from itself.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          None\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Class methods inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  dataspecs() -> 'Dict[str, DataSpec]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all ``DataSpec`` properties on this class.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of ``DataSpec`` properties\n",
      "     |  \n",
      "     |  lookup(name: 'str', *, raises: 'bool' = True) -> 'PropertyDescriptor[Any] | None' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Find the ``PropertyDescriptor`` for a Bokeh property on a class,\n",
      "     |      given the property name.\n",
      "     |      \n",
      "     |      Args:\n",
      "     |          name (str) : name of the property to search for\n",
      "     |          raises (bool) : whether to raise or return None if missing\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          PropertyDescriptor : descriptor for property named ``name``\n",
      "     |  \n",
      "     |  properties(*, _with_props: 'bool' = False) -> 'Union[Set[str], Dict[str, Property[Any]]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of properties on this class.\n",
      "     |      \n",
      "     |      .. warning::\n",
      "     |          In a future version of Bokeh, this method will return a dictionary\n",
      "     |          mapping property names to property objects. To future-proof this\n",
      "     |          current usage of this method, wrap the return value in ``list``.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          property names\n",
      "     |  \n",
      "     |  properties_with_refs() -> 'Dict[str, Property[Any]]' from bokeh.core.has_props.MetaHasProps\n",
      "     |      Collect the names of all properties on this class that also have\n",
      "     |      references.\n",
      "     |      \n",
      "     |      This method *always* traverses the class hierarchy and includes\n",
      "     |      properties defined on any parent classes.\n",
      "     |      \n",
      "     |      Returns:\n",
      "     |          set[str] : names of properties that have references\n",
      "     |  \n",
      "     |  static_to_serializable(serializer: 'StaticSerializer') -> 'ModelRef' from bokeh.core.has_props.MetaHasProps\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.core.has_props.HasProps:\n",
      "     |  \n",
      "     |  __dict__\n",
      "     |      dictionary for instance variables (if defined)\n",
      "     |  \n",
      "     |  __weakref__\n",
      "     |      list of weak references to the object (if defined)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Data descriptors inherited from bokeh.model.util.HasDocumentRef:\n",
      "     |  \n",
      "     |  document\n",
      "     |      The |Document| this model is attached to (can be ``None``)\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.PropertyCallbackManager:\n",
      "     |  \n",
      "     |  remove_on_change(self, attr: 'str', *callbacks: 'PropertyCallback') -> 'None'\n",
      "     |      Remove a callback from this object\n",
      "     |  \n",
      "     |  ----------------------------------------------------------------------\n",
      "     |  Methods inherited from bokeh.util.callback_manager.EventCallbackManager:\n",
      "     |  \n",
      "     |  on_event(self, event: 'str | Type[Event]', *callbacks: 'EventCallback') -> 'None'\n",
      "     |      Run callbacks when the specified event occurs on this Model\n",
      "     |      \n",
      "     |      Not all Events are supported for all Models.\n",
      "     |      See specific Events in :ref:`bokeh.events` for more information on\n",
      "     |      which Models are able to trigger them.\n",
      "\n",
      "DATA\n",
      "    __all__ = ('BooleanFilter', 'CustomJSFilter', 'Filter', 'GroupFilter',...\n",
      "\n",
      "FILE\n",
      "    c:\\programdata\\anaconda3\\lib\\site-packages\\bokeh\\models\\filters.py\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# 以filters为例：\n",
    "help(bokeh.models.filters)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4d048eaf",
   "metadata": {},
   "source": [
    "# 绘图"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "74b2d955",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "    <div class=\"bk-root\">\n",
       "        <a href=\"https://bokeh.org\" target=\"_blank\" class=\"bk-logo bk-logo-small bk-logo-notebook\"></a>\n",
       "        <span id=\"1003\">Loading BokehJS ...</span>\n",
       "    </div>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "(function(root) {\n",
       "  function now() {\n",
       "    return new Date();\n",
       "  }\n",
       "\n",
       "  const force = true;\n",
       "\n",
       "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
       "    root._bokeh_onload_callbacks = [];\n",
       "    root._bokeh_is_loading = undefined;\n",
       "  }\n",
       "\n",
       "  const JS_MIME_TYPE = 'application/javascript';\n",
       "  const HTML_MIME_TYPE = 'text/html';\n",
       "  const EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
       "  const CLASS_NAME = 'output_bokeh rendered_html';\n",
       "\n",
       "  /**\n",
       "   * Render data to the DOM node\n",
       "   */\n",
       "  function render(props, node) {\n",
       "    const script = document.createElement(\"script\");\n",
       "    node.appendChild(script);\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when an output is cleared or removed\n",
       "   */\n",
       "  function handleClearOutput(event, handle) {\n",
       "    const cell = handle.cell;\n",
       "\n",
       "    const id = cell.output_area._bokeh_element_id;\n",
       "    const server_id = cell.output_area._bokeh_server_id;\n",
       "    // Clean up Bokeh references\n",
       "    if (id != null && id in Bokeh.index) {\n",
       "      Bokeh.index[id].model.document.clear();\n",
       "      delete Bokeh.index[id];\n",
       "    }\n",
       "\n",
       "    if (server_id !== undefined) {\n",
       "      // Clean up Bokeh references\n",
       "      const cmd_clean = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
       "      cell.notebook.kernel.execute(cmd_clean, {\n",
       "        iopub: {\n",
       "          output: function(msg) {\n",
       "            const id = msg.content.text.trim();\n",
       "            if (id in Bokeh.index) {\n",
       "              Bokeh.index[id].model.document.clear();\n",
       "              delete Bokeh.index[id];\n",
       "            }\n",
       "          }\n",
       "        }\n",
       "      });\n",
       "      // Destroy server and session\n",
       "      const cmd_destroy = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
       "      cell.notebook.kernel.execute(cmd_destroy);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  /**\n",
       "   * Handle when a new output is added\n",
       "   */\n",
       "  function handleAddOutput(event, handle) {\n",
       "    const output_area = handle.output_area;\n",
       "    const output = handle.output;\n",
       "\n",
       "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
       "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
       "      return\n",
       "    }\n",
       "\n",
       "    const toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
       "\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
       "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
       "      // store reference to embed id on output_area\n",
       "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
       "    }\n",
       "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
       "      const bk_div = document.createElement(\"div\");\n",
       "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
       "      const script_attrs = bk_div.children[0].attributes;\n",
       "      for (let i = 0; i < script_attrs.length; i++) {\n",
       "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
       "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
       "      }\n",
       "      // store reference to server id on output_area\n",
       "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
       "    }\n",
       "  }\n",
       "\n",
       "  function register_renderer(events, OutputArea) {\n",
       "\n",
       "    function append_mime(data, metadata, element) {\n",
       "      // create a DOM node to render to\n",
       "      const toinsert = this.create_output_subarea(\n",
       "        metadata,\n",
       "        CLASS_NAME,\n",
       "        EXEC_MIME_TYPE\n",
       "      );\n",
       "      this.keyboard_manager.register_events(toinsert);\n",
       "      // Render to node\n",
       "      const props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
       "      render(props, toinsert[toinsert.length - 1]);\n",
       "      element.append(toinsert);\n",
       "      return toinsert\n",
       "    }\n",
       "\n",
       "    /* Handle when an output is cleared or removed */\n",
       "    events.on('clear_output.CodeCell', handleClearOutput);\n",
       "    events.on('delete.Cell', handleClearOutput);\n",
       "\n",
       "    /* Handle when a new output is added */\n",
       "    events.on('output_added.OutputArea', handleAddOutput);\n",
       "\n",
       "    /**\n",
       "     * Register the mime type and append_mime function with output_area\n",
       "     */\n",
       "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
       "      /* Is output safe? */\n",
       "      safe: true,\n",
       "      /* Index of renderer in `output_area.display_order` */\n",
       "      index: 0\n",
       "    });\n",
       "  }\n",
       "\n",
       "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
       "  if (root.Jupyter !== undefined) {\n",
       "    const events = require('base/js/events');\n",
       "    const OutputArea = require('notebook/js/outputarea').OutputArea;\n",
       "\n",
       "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
       "      register_renderer(events, OutputArea);\n",
       "    }\n",
       "  }\n",
       "\n",
       "  \n",
       "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
       "    root._bokeh_timeout = Date.now() + 5000;\n",
       "    root._bokeh_failed_load = false;\n",
       "  }\n",
       "\n",
       "  const NB_LOAD_WARNING = {'data': {'text/html':\n",
       "     \"<div style='background-color: #fdd'>\\n\"+\n",
       "     \"<p>\\n\"+\n",
       "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
       "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
       "     \"</p>\\n\"+\n",
       "     \"<ul>\\n\"+\n",
       "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
       "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
       "     \"</ul>\\n\"+\n",
       "     \"<code>\\n\"+\n",
       "     \"from bokeh.resources import INLINE\\n\"+\n",
       "     \"output_notebook(resources=INLINE)\\n\"+\n",
       "     \"</code>\\n\"+\n",
       "     \"</div>\"}};\n",
       "\n",
       "  function display_loaded() {\n",
       "    const el = document.getElementById(\"1003\");\n",
       "    if (el != null) {\n",
       "      el.textContent = \"BokehJS is loading...\";\n",
       "    }\n",
       "    if (root.Bokeh !== undefined) {\n",
       "      if (el != null) {\n",
       "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
       "      }\n",
       "    } else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(display_loaded, 100)\n",
       "    }\n",
       "  }\n",
       "\n",
       "\n",
       "  function run_callbacks() {\n",
       "    try {\n",
       "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
       "        if (callback != null)\n",
       "          callback();\n",
       "      });\n",
       "    } finally {\n",
       "      delete root._bokeh_onload_callbacks\n",
       "    }\n",
       "    console.debug(\"Bokeh: all callbacks have finished\");\n",
       "  }\n",
       "\n",
       "  function load_libs(css_urls, js_urls, callback) {\n",
       "    if (css_urls == null) css_urls = [];\n",
       "    if (js_urls == null) js_urls = [];\n",
       "\n",
       "    root._bokeh_onload_callbacks.push(callback);\n",
       "    if (root._bokeh_is_loading > 0) {\n",
       "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
       "      return null;\n",
       "    }\n",
       "    if (js_urls == null || js_urls.length === 0) {\n",
       "      run_callbacks();\n",
       "      return null;\n",
       "    }\n",
       "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
       "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
       "\n",
       "    function on_load() {\n",
       "      root._bokeh_is_loading--;\n",
       "      if (root._bokeh_is_loading === 0) {\n",
       "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
       "        run_callbacks()\n",
       "      }\n",
       "    }\n",
       "\n",
       "    function on_error(url) {\n",
       "      console.error(\"failed to load \" + url);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < css_urls.length; i++) {\n",
       "      const url = css_urls[i];\n",
       "      const element = document.createElement(\"link\");\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.rel = \"stylesheet\";\n",
       "      element.type = \"text/css\";\n",
       "      element.href = url;\n",
       "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
       "      document.body.appendChild(element);\n",
       "    }\n",
       "\n",
       "    for (let i = 0; i < js_urls.length; i++) {\n",
       "      const url = js_urls[i];\n",
       "      const element = document.createElement('script');\n",
       "      element.onload = on_load;\n",
       "      element.onerror = on_error.bind(null, url);\n",
       "      element.async = false;\n",
       "      element.src = url;\n",
       "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
       "      document.head.appendChild(element);\n",
       "    }\n",
       "  };\n",
       "\n",
       "  function inject_raw_css(css) {\n",
       "    const element = document.createElement(\"style\");\n",
       "    element.appendChild(document.createTextNode(css));\n",
       "    document.body.appendChild(element);\n",
       "  }\n",
       "\n",
       "  \n",
       "  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.2.min.js\"];\n",
       "  const css_urls = [];\n",
       "  \n",
       "\n",
       "  const inline_js = [\n",
       "    function(Bokeh) {\n",
       "      Bokeh.set_log_level(\"info\");\n",
       "    },\n",
       "    function(Bokeh) {\n",
       "    \n",
       "    \n",
       "    }\n",
       "  ];\n",
       "\n",
       "  function run_inline_js() {\n",
       "    \n",
       "    if (root.Bokeh !== undefined || force === true) {\n",
       "      \n",
       "    for (let i = 0; i < inline_js.length; i++) {\n",
       "      inline_js[i].call(root, root.Bokeh);\n",
       "    }\n",
       "    if (force === true) {\n",
       "        display_loaded();\n",
       "      }} else if (Date.now() < root._bokeh_timeout) {\n",
       "      setTimeout(run_inline_js, 100);\n",
       "    } else if (!root._bokeh_failed_load) {\n",
       "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
       "      root._bokeh_failed_load = true;\n",
       "    } else if (force !== true) {\n",
       "      const cell = $(document.getElementById(\"1003\")).parents('.cell').data().cell;\n",
       "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
       "    }\n",
       "\n",
       "  }\n",
       "\n",
       "  if (root._bokeh_is_loading === 0) {\n",
       "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
       "    run_inline_js();\n",
       "  } else {\n",
       "    load_libs(css_urls, js_urls, function() {\n",
       "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
       "      run_inline_js();\n",
       "    });\n",
       "  }\n",
       "}(window));"
      ],
      "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  const NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    const el = document.getElementById(\"1003\");\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  const js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.4.2.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-mathjax-2.4.2.min.js\"];\n  const css_urls = [];\n  \n\n  const inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (let i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    if (force === true) {\n        display_loaded();\n      }} else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      const cell = $(document.getElementById(\"1003\")).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"73356d43-4185-4a13-91e4-ebebc8b27112\" data-root-id=\"1457\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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       "  function embed_document(root) {\n",
       "    \n",
       "  const docs_json = 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\"},\"id\":\"1278\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"1241\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1328\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1282\",\"type\":\"DataRange1d\"},{\"attributes\":{\"end_angle\":{\"value\":4.1},\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"#8888ee\"},\"hatch_alpha\":{\"value\":0.2},\"hatch_color\":{\"value\":\"#8888ee\"},\"inner_radius\":{\"units\":\"screen\",\"value\":10},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"#8888ee\"},\"outer_radius\":{\"units\":\"screen\",\"value\":20},\"start_angle\":{\"value\":0.6},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1040\",\"type\":\"AnnularWedge\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"1037\"},\"glyph\":{\"id\":\"1038\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"1040\"},\"nonselection_glyph\":{\"id\":\"1039\"},\"view\":{\"id\":\"1042\"}},\"id\":\"1041\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1357\"},\"group\":null,\"major_label_policy\":{\"id\":\"1358\"},\"ticker\":{\"id\":\"1020\"}},\"id\":\"1019\",\"type\":\"LinearAxis\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1434\"},\"group\":null,\"major_label_policy\":{\"id\":\"1435\"},\"ticker\":{\"id\":\"1293\"}},\"id\":\"1292\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1323\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1439\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"1325\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1438\",\"type\":\"AllLabels\"},{\"attributes\":{\"below\":[{\"id\":\"1054\"}],\"center\":[{\"id\":\"1057\"},{\"id\":\"1061\"}],\"height\":200,\"left\":[{\"id\":\"1058\"}],\"renderers\":[{\"id\":\"1080\"}],\"title\":{\"id\":\"1044\"},\"toolbar\":{\"id\":\"1069\"},\"toolbar_location\":null,\"width\":200,\"x_range\":{\"id\":\"1046\"},\"x_scale\":{\"id\":\"1050\"},\"y_range\":{\"id\":\"1048\"},\"y_scale\":{\"id\":\"1052\"}},\"id\":\"1043\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1435\",\"type\":\"AllLabels\"},{\"attributes\":{},\"id\":\"1289\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1332\",\"type\":\"BasicTicker\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1448\"},\"group\":null,\"major_label_policy\":{\"id\":\"1449\"},\"ticker\":{\"id\":\"1328\"}},\"id\":\"1327\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1437\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1423\"},\"group\":null,\"major_label_policy\":{\"id\":\"1424\"},\"ticker\":{\"id\":\"1254\"}},\"id\":\"1253\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1284\",\"type\":\"LinearScale\"},{\"attributes\":{\"coordinates\":null,\"group\":null,\"text\":\"annulus\"},\"id\":\"1044\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"1286\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis\":{\"id\":\"1327\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"1330\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1250\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1440\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"1048\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"1293\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1245\",\"type\":\"LinearScale\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1437\"},\"group\":null,\"major_label_policy\":{\"id\":\"1438\"},\"ticker\":{\"id\":\"1289\"}},\"id\":\"1288\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"1371\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1448\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1335\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"1247\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis\":{\"id\":\"1015\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"1018\",\"type\":\"Grid\"},{\"attributes\":{\"axis\":{\"id\":\"1288\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"1291\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1055\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"1254\",\"type\":\"BasicTicker\"},{\"attributes\":{\"below\":[{\"id\":\"1327\"}],\"center\":[{\"id\":\"1330\"},{\"id\":\"1334\"}],\"height\":200,\"left\":[{\"id\":\"1331\"}],\"renderers\":[{\"id\":\"1353\"}],\"title\":{\"id\":\"1317\"},\"toolbar\":{\"id\":\"1342\"},\"toolbar_location\":null,\"width\":200,\"x_range\":{\"id\":\"1319\"},\"x_scale\":{\"id\":\"1323\"},\"y_range\":{\"id\":\"1321\"},\"y_scale\":{\"id\":\"1325\"}},\"id\":\"1316\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{},\"id\":\"1336\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"1426\"},\"group\":null,\"major_label_policy\":{\"id\":\"1427\"},\"ticker\":{\"id\":\"1250\"}},\"id\":\"1249\",\"type\":\"LinearAxis\"},{\"attributes\":{\"data\":{\"x\":{\"__ndarray__\":\"AAAAAAAAAMAAAAAAAAD4vwAAAAAAAPC/AAAAAAAA4L8AAAAAAAAAAAAAAAAAAOA/AAAAAAAA8D8AAAAAAAD4PwAAAAAAAABA\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[9]},\"y\":{\"__ndarray__\":\"AAAAAAAAEEAAAAAAAAACQAAAAAAAAPA/AAAAAAAA0D8AAAAAAAAAAAAAAAAAANA/AAAAAAAA8D8AAAAAAAACQAAAAAAAABBA\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[9]}},\"selected\":{\"id\":\"1374\"},\"selection_policy\":{\"id\":\"1373\"}},\"id\":\"1076\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"overlay\":{\"id\":\"1341\"}},\"id\":\"1337\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"1013\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1050\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"1445\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1052\",\"type\":\"LinearScale\"},{\"attributes\":{\"axis\":{\"id\":\"1249\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"1252\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1446\",\"type\":\"AllLabels\"},{\"attributes\":{\"axis\":{\"id\":\"1054\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"1057\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"1338\",\"type\":\"SaveTool\"}],\"root_ids\":[\"1457\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.2\"}};\n",
       "  const render_items = [{\"docid\":\"d44f5eed-befb-4fd7-9df7-726e394f2259\",\"root_ids\":[\"1457\"],\"roots\":{\"1457\":\"73356d43-4185-4a13-91e4-ebebc8b27112\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1457"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "from bokeh.layouts import gridplot\n",
    "from bokeh.plotting import figure, show, output_notebook\n",
    "output_notebook()\n",
    "\n",
    "#数据\n",
    "N=9\n",
    "x=np.linspace(-2, 2, N)\n",
    "y=x**2\n",
    "sizes = np.linspace(10, 20, N)\n",
    "xpts = np.array([-.09, -.12, .0, .12, .09])\n",
    "ypts = np.array([-.1, .02, .1, .02, -.1])\n",
    "#画布列表\n",
    "figures = []\n",
    "\n",
    "# 1. annular_wedge环状楔\n",
    "p = figure(title=\"annular_wedge\")\n",
    "p.annular_wedge(x, y, 10, 20, 0.6, 4.1, color=\"#8888ee\",inner_radius_units=\"screen\", outer_radius_units=\"screen\")\n",
    "figures.append(p)\n",
    "\n",
    "# 2. annulus环状\n",
    "p = figure(title=\"annulus\")\n",
    "p.annulus(x, y, 10, 20,  color=\"#7FC97F\",inner_radius_units=\"screen\", outer_radius_units=\"screen\")\n",
    "figures.append(p)\n",
    "\n",
    "# 3.弧形arc\n",
    "p = figure(title=\"arc\")\n",
    "p.arc(x, y,20, 0.6, 4.1,radius_units = \"screen\" , color=\"#BEAED4\",line_width=3)\n",
    "figures.append(p)\n",
    "\n",
    "\n",
    "# 4. 贝塞尔曲线bezier\n",
    "p = figure(title= \"bezier\")\n",
    "p.bezier(x, y, x+0.2, y, x+0.1, y+0.1,x-0.1, y-0.1,color=\"#8073AC\", line_width=2)\n",
    "figures.append(p)\n",
    "\n",
    "# 5.圆circle\n",
    "p = figure(title=\"circle\")\n",
    "p.circle(x, y, radius=0.1, color=\"#3288BD\")\n",
    "figures.append(p)\n",
    "\n",
    "# 6.线line\n",
    "p = figure(title=\"line\")\n",
    "p.line(x, y, color= \"#F46D43\")\n",
    "figures.append(p)\n",
    "\n",
    "# 7.多线multi_line\n",
    "p = figure(title= \"multi_line\")\n",
    "p.multi_line([xpts+xx for xx in x],[ypts+yy for yy in y], color=\"#8073AC\",line_width=2)\n",
    "figures.append(p)\n",
    "\n",
    "# 8.椭圆形ellipse \n",
    "p = figure(title=\"ellipse \")\n",
    "p.ellipse (x,y,15,25, angle=-0.7, color=\"#1D91C0\",width_units=\"screen\", height_units=\"screen\")\n",
    "figures.append(p)\n",
    "\n",
    "# 9. patch\n",
    "p = figure(title=\"patch\" )\n",
    "p.patch(x,y,color=\"#F46D43\")\n",
    "figures.append(p)\n",
    "\n",
    "# 网格展示\n",
    "show(gridplot(figures,ncols=4,width=200,height=200))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3cd4420e",
   "metadata": {},
   "source": [
    "# 散点图scatter"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38e2e02d",
   "metadata": {},
   "source": [
    "- 属性参数\n",
    "> 1. x:x坐标\n",
    "> 1. y:y坐标\n",
    "> 1. size:离散点点大小\n",
    "> 1. marker:离散点点标记名称\n",
    "> 1. color:填充及轮廓线颜色\n",
    "> 1. alpha:透明度\n",
    "> 1.**kwargs:线属性和填充属性\n",
    "> 1.source:用户提供的数据源。如果需要，将尝试将对象转换为ColumnDataSource 。如果没有提供，则会自动为用户创建一个。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "02daf6d0",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"ab73ea17-8b40-4341-b95c-0dc5f01c0989\" data-root-id=\"1998\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  const docs_json = {\"4481ce03-80d2-452d-bac0-80b31dcdb354\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"2007\"}],\"center\":[{\"id\":\"2010\"},{\"id\":\"2014\"}],\"height\":400,\"left\":[{\"id\":\"2011\"}],\"renderers\":[{\"id\":\"2033\"},{\"id\":\"2039\"}],\"title\":{\"id\":\"2131\"},\"toolbar\":{\"id\":\"2022\"},\"width\":400,\"x_range\":{\"id\":\"1999\"},\"x_scale\":{\"id\":\"2003\"},\"y_range\":{\"id\":\"2001\"},\"y_scale\":{\"id\":\"2005\"}},\"id\":\"1998\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"overlay\":{\"id\":\"2021\"}},\"id\":\"2017\",\"type\":\"BoxZoomTool\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.1},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"size\":{\"value\":20},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2037\",\"type\":\"Circle\"},{\"attributes\":{\"fill_color\":{\"value\":\"red\"},\"line_color\":{\"value\":\"#1f77b4\"},\"marker\":{\"value\":\"square\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2030\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"2139\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"2035\"},\"glyph\":{\"id\":\"2036\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"2038\"},\"nonselection_glyph\":{\"id\":\"2037\"},\"view\":{\"id\":\"2040\"}},\"id\":\"2039\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2012\",\"type\":\"BasicTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.2},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"navy\"},\"size\":{\"value\":20},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2038\",\"type\":\"Circle\"},{\"attributes\":{\"bottom_units\":\"screen\",\"coordinates\":null,\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"group\":null,\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"2021\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"tools\":[{\"id\":\"2015\"},{\"id\":\"2016\"},{\"id\":\"2017\"},{\"id\":\"2018\"},{\"id\":\"2019\"},{\"id\":\"2020\"}]},\"id\":\"2022\",\"type\":\"Toolbar\"},{\"attributes\":{},\"id\":\"2018\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"2019\",\"type\":\"ResetTool\"},{\"attributes\":{\"data\":{\"x\":[1,2,3,4,5],\"y\":[6,7,2,4,5]},\"selected\":{\"id\":\"2142\"},\"selection_policy\":{\"id\":\"2141\"}},\"id\":\"2035\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"2035\"}},\"id\":\"2040\",\"type\":\"CDSView\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"2134\"},\"group\":null,\"major_label_policy\":{\"id\":\"2135\"},\"ticker\":{\"id\":\"2012\"}},\"id\":\"2011\",\"type\":\"LinearAxis\"},{\"attributes\":{\"coordinates\":null,\"group\":null},\"id\":\"2131\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"2141\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"axis\":{\"id\":\"2011\"},\"coordinates\":null,\"dimension\":1,\"group\":null,\"ticker\":null},\"id\":\"2014\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"2142\",\"type\":\"Selection\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"red\"},\"hatch_alpha\":{\"value\":0.1},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"#1f77b4\"},\"marker\":{\"value\":\"square\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2031\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"2020\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"1999\",\"type\":\"DataRange1d\"},{\"attributes\":{\"source\":{\"id\":\"2029\"}},\"id\":\"2034\",\"type\":\"CDSView\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"2029\"},\"glyph\":{\"id\":\"2030\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"2032\"},\"nonselection_glyph\":{\"id\":\"2031\"},\"view\":{\"id\":\"2034\"}},\"id\":\"2033\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"2137\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"red\"},\"hatch_alpha\":{\"value\":0.2},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"#1f77b4\"},\"marker\":{\"value\":\"square\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2032\",\"type\":\"Scatter\"},{\"attributes\":{\"axis\":{\"id\":\"2007\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"2010\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"2001\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"2003\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"2134\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"2008\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"2138\",\"type\":\"AllLabels\"},{\"attributes\":{\"data\":{\"x\":[1,2,3],\"y\":[4,5,6]},\"selected\":{\"id\":\"2140\"},\"selection_policy\":{\"id\":\"2139\"}},\"id\":\"2029\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.5},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.5},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.5},\"line_color\":{\"value\":\"navy\"},\"size\":{\"value\":20},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"2036\",\"type\":\"Circle\"},{\"attributes\":{},\"id\":\"2015\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"2005\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"2016\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"2140\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"2135\",\"type\":\"AllLabels\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"2137\"},\"group\":null,\"major_label_policy\":{\"id\":\"2138\"},\"ticker\":{\"id\":\"2008\"}},\"id\":\"2007\",\"type\":\"LinearAxis\"}],\"root_ids\":[\"1998\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.2\"}};\n",
       "  const render_items = [{\"docid\":\"4481ce03-80d2-452d-bac0-80b31dcdb354\",\"root_ids\":[\"1998\"],\"roots\":{\"1998\":\"ab73ea17-8b40-4341-b95c-0dc5f01c0989\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "1998"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 数据\n",
    "x = [1, 2, 3, 4, 5]\n",
    "y = [6, 7, 2, 4, 5]\n",
    "# 画布：尺寸\n",
    "p = figure(plot_width=400, plot_height=400)\n",
    "# 画图\n",
    "# data-space units  坐标轴单位\n",
    "# screen units  显示器像素单位\n",
    "p.scatter([1,2,3],[4,5,6], marker=\"square\", fill_color=\"red\")\n",
    "p.circle(x, y, size=20, color=\"navy\", alpha=0.5)\n",
    "# 显示\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "52e878bf",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"e929ffc0-706d-4b56-98fb-d0d9a85f15af\" data-root-id=\"6016\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  const docs_json = {\"0d0ce60f-e1e0-45c2-b361-8791e5ccab43\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"6027\"}],\"center\":[{\"id\":\"6030\"},{\"id\":\"6034\"}],\"height\":300,\"left\":[{\"id\":\"6031\"}],\"renderers\":[{\"id\":\"6053\"}],\"title\":{\"id\":\"6017\"},\"toolbar\":{\"id\":\"6042\"},\"width\":300,\"x_range\":{\"id\":\"6019\"},\"x_scale\":{\"id\":\"6023\"},\"y_range\":{\"id\":\"6021\"},\"y_scale\":{\"id\":\"6025\"}},\"id\":\"6016\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"6049\"},\"glyph\":{\"id\":\"6050\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"6052\"},\"nonselection_glyph\":{\"id\":\"6051\"},\"view\":{\"id\":\"6054\"}},\"id\":\"6053\",\"type\":\"GlyphRenderer\"},{\"attributes\":{},\"id\":\"6036\",\"type\":\"WheelZoomTool\"},{\"attributes\":{\"overlay\":{\"id\":\"6041\"}},\"id\":\"6037\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"6039\",\"type\":\"ResetTool\"},{\"attributes\":{},\"id\":\"6038\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"6028\",\"type\":\"BasicTicker\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.2},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"value\":15},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6052\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6023\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"6040\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"6311\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"6313\",\"type\":\"UnionRenderers\"},{\"attributes\":{},\"id\":\"6025\",\"type\":\"LinearScale\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"6311\"},\"group\":null,\"major_label_policy\":{\"id\":\"6312\"},\"ticker\":{\"id\":\"6028\"}},\"id\":\"6027\",\"type\":\"LinearAxis\"},{\"attributes\":{\"tools\":[{\"id\":\"6035\"},{\"id\":\"6036\"},{\"id\":\"6037\"},{\"id\":\"6038\"},{\"id\":\"6039\"},{\"id\":\"6040\"}]},\"id\":\"6042\",\"type\":\"Toolbar\"},{\"attributes\":{\"axis\":{\"id\":\"6027\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"6030\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"6032\",\"type\":\"BasicTicker\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"6308\"},\"group\":null,\"major_label_policy\":{\"id\":\"6309\"},\"ticker\":{\"id\":\"6032\"}},\"id\":\"6031\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"6314\",\"type\":\"Selection\"},{\"attributes\":{\"bottom_units\":\"screen\",\"coordinates\":null,\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"group\":null,\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"6041\",\"type\":\"BoxAnnotation\"},{\"attributes\":{\"axis\":{\"id\":\"6031\"},\"coordinates\":null,\"dimension\":1,\"group\":null,\"ticker\":null},\"id\":\"6034\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"6021\",\"type\":\"DataRange1d\"},{\"attributes\":{},\"id\":\"6308\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"6019\",\"type\":\"DataRange1d\"},{\"attributes\":{\"data\":{\"x\":[1,2,3,4],\"y\":[2,4,6,8]},\"selected\":{\"id\":\"6314\"},\"selection_policy\":{\"id\":\"6313\"}},\"id\":\"6049\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.1},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"value\":15},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6051\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6312\",\"type\":\"AllLabels\"},{\"attributes\":{\"coordinates\":null,\"group\":null,\"text\":\"\\u6c14\\u6ce1\\u56fe\"},\"id\":\"6017\",\"type\":\"Title\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":\"navy\"},\"hatch_alpha\":{\"value\":0.2},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"value\":15},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6050\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6309\",\"type\":\"AllLabels\"},{\"attributes\":{},\"id\":\"6035\",\"type\":\"PanTool\"},{\"attributes\":{\"source\":{\"id\":\"6049\"}},\"id\":\"6054\",\"type\":\"CDSView\"}],\"root_ids\":[\"6016\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.2\"}};\n",
       "  const render_items = [{\"docid\":\"0d0ce60f-e1e0-45c2-b361-8791e5ccab43\",\"root_ids\":[\"6016\"],\"roots\":{\"6016\":\"e929ffc0-706d-4b56-98fb-d0d9a85f15af\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "6016"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "x=[1,2,3,4]\n",
    "y=[2,4,6,8]\n",
    "sizes = 15\n",
    "p = figure(title=\"气泡图\",plot_width=300, plot_height=300)\n",
    "# 气泡图仍采用散点图画法\n",
    "p.scatter(x, y, \n",
    "          marker=\"circle\", size=sizes, color=\"navy\",\n",
    "          line_width=2,alpha=0.2\n",
    "         )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "482838f3",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"a0a591f2-aacb-42ab-b97d-55964d04cddd\" data-root-id=\"6729\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  const docs_json = {\"314d9d42-13ad-4124-aa21-4f02954a7dc6\":{\"defs\":[],\"roots\":{\"references\":[{\"attributes\":{\"below\":[{\"id\":\"6740\"}],\"center\":[{\"id\":\"6743\"},{\"id\":\"6747\"}],\"left\":[{\"id\":\"6744\"}],\"renderers\":[{\"id\":\"6766\"}],\"title\":{\"id\":\"6730\"},\"toolbar\":{\"id\":\"6755\"},\"x_range\":{\"id\":\"6732\"},\"x_scale\":{\"id\":\"6736\"},\"y_range\":{\"id\":\"6734\"},\"y_scale\":{\"id\":\"6738\"}},\"id\":\"6729\",\"subtype\":\"Figure\",\"type\":\"Plot\"},{\"attributes\":{\"axis\":{\"id\":\"6744\"},\"coordinates\":null,\"dimension\":1,\"group\":null,\"ticker\":null},\"id\":\"6747\",\"type\":\"Grid\"},{\"attributes\":{},\"id\":\"7041\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"7044\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{\"axis\":{\"id\":\"6740\"},\"coordinates\":null,\"group\":null,\"ticker\":null},\"id\":\"6743\",\"type\":\"Grid\"},{\"attributes\":{\"fill_color\":{\"value\":null},\"hatch_color\":{\"value\":\"navy\"},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"field\":\"size\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6763\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6738\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"6741\",\"type\":\"BasicTicker\"},{\"attributes\":{},\"id\":\"7045\",\"type\":\"AllLabels\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"7041\"},\"group\":null,\"major_label_policy\":{\"id\":\"7042\"},\"ticker\":{\"id\":\"6745\"}},\"id\":\"6744\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"6732\",\"type\":\"DataRange1d\"},{\"attributes\":{\"overlay\":{\"id\":\"6754\"}},\"id\":\"6750\",\"type\":\"BoxZoomTool\"},{\"attributes\":{},\"id\":\"7047\",\"type\":\"Selection\"},{\"attributes\":{},\"id\":\"6753\",\"type\":\"HelpTool\"},{\"attributes\":{},\"id\":\"6752\",\"type\":\"ResetTool\"},{\"attributes\":{\"coordinates\":null,\"group\":null,\"text\":\"\\u6c14\\u6ce1\\u56fe2\"},\"id\":\"6730\",\"type\":\"Title\"},{\"attributes\":{},\"id\":\"6751\",\"type\":\"SaveTool\"},{\"attributes\":{},\"id\":\"6748\",\"type\":\"PanTool\"},{\"attributes\":{},\"id\":\"6736\",\"type\":\"LinearScale\"},{\"attributes\":{},\"id\":\"7046\",\"type\":\"UnionRenderers\"},{\"attributes\":{\"source\":{\"id\":\"6762\"}},\"id\":\"6767\",\"type\":\"CDSView\"},{\"attributes\":{\"data\":{\"size\":{\"__ndarray__\":\"CgAAABQAAAAeAAAAKAAAAA==\",\"dtype\":\"int32\",\"order\":\"little\",\"shape\":[4]},\"x\":[1,2,3,4],\"y\":[2,4,6,8]},\"selected\":{\"id\":\"7047\"},\"selection_policy\":{\"id\":\"7046\"}},\"id\":\"6762\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"value\":null},\"hatch_alpha\":{\"value\":0.1},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"field\":\"size\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6764\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6749\",\"type\":\"WheelZoomTool\"},{\"attributes\":{},\"id\":\"6734\",\"type\":\"DataRange1d\"},{\"attributes\":{\"coordinates\":null,\"formatter\":{\"id\":\"7044\"},\"group\":null,\"major_label_policy\":{\"id\":\"7045\"},\"ticker\":{\"id\":\"6741\"}},\"id\":\"6740\",\"type\":\"LinearAxis\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.2},\"fill_color\":{\"value\":null},\"hatch_alpha\":{\"value\":0.2},\"hatch_color\":{\"value\":\"navy\"},\"line_alpha\":{\"value\":0.2},\"line_color\":{\"value\":\"navy\"},\"line_width\":{\"value\":2},\"size\":{\"field\":\"size\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"6765\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"6745\",\"type\":\"BasicTicker\"},{\"attributes\":{\"bottom_units\":\"screen\",\"coordinates\":null,\"fill_alpha\":0.5,\"fill_color\":\"lightgrey\",\"group\":null,\"left_units\":\"screen\",\"level\":\"overlay\",\"line_alpha\":1.0,\"line_color\":\"black\",\"line_dash\":[4,4],\"line_width\":2,\"right_units\":\"screen\",\"syncable\":false,\"top_units\":\"screen\"},\"id\":\"6754\",\"type\":\"BoxAnnotation\"},{\"attributes\":{},\"id\":\"7042\",\"type\":\"AllLabels\"},{\"attributes\":{\"coordinates\":null,\"data_source\":{\"id\":\"6762\"},\"glyph\":{\"id\":\"6763\"},\"group\":null,\"hover_glyph\":null,\"muted_glyph\":{\"id\":\"6765\"},\"nonselection_glyph\":{\"id\":\"6764\"},\"view\":{\"id\":\"6767\"}},\"id\":\"6766\",\"type\":\"GlyphRenderer\"},{\"attributes\":{\"tools\":[{\"id\":\"6748\"},{\"id\":\"6749\"},{\"id\":\"6750\"},{\"id\":\"6751\"},{\"id\":\"6752\"},{\"id\":\"6753\"}]},\"id\":\"6755\",\"type\":\"Toolbar\"}],\"root_ids\":[\"6729\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.2\"}};\n",
       "  const render_items = [{\"docid\":\"314d9d42-13ad-4124-aa21-4f02954a7dc6\",\"root_ids\":[\"6729\"],\"roots\":{\"6729\":\"a0a591f2-aacb-42ab-b97d-55964d04cddd\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "6729"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 简单气泡图\n",
    "x=[1,2,3,4]\n",
    "y=[2,4,6,8]\n",
    "sizes = np.array(y)*5 # 气泡大小\n",
    "p = figure(title=\"气泡图2\")\n",
    "p.scatter(x, y, \n",
    "          marker=\"circle\", size=sizes, color=\"navy\",\n",
    "          fill_color=None, line_width=2\n",
    "         )\n",
    "show(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0cbd88fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "\n",
       "  <div class=\"bk-root\" id=\"5346d261-3c27-4df5-a748-b84416637501\" data-root-id=\"2544\"></div>\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "(function(root) {\n",
       "  function embed_document(root) {\n",
       "    \n",
       "  const docs_json = 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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"little\",\"shape\":[4000]},\"x\":{\"__ndarray__\":\"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\",\"dtype\":\"float64\",\"order\":\"lit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":\"2471\"}},\"id\":\"2470\",\"type\":\"LinearAxis\"},{\"attributes\":{},\"id\":\"2466\",\"type\":\"LinearScale\"}],\"root_ids\":[\"2544\"]},\"title\":\"Bokeh Application\",\"version\":\"2.4.2\"}};\n",
       "  const render_items = [{\"docid\":\"b38f910b-c81a-4e3d-9a07-d7278e81d136\",\"root_ids\":[\"2544\"],\"roots\":{\"2544\":\"5346d261-3c27-4df5-a748-b84416637501\"}}];\n",
       "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
       "\n",
       "  }\n",
       "  if (root.Bokeh !== undefined) {\n",
       "    embed_document(root);\n",
       "  } else {\n",
       "    let attempts = 0;\n",
       "    const timer = setInterval(function(root) {\n",
       "      if (root.Bokeh !== undefined) {\n",
       "        clearInterval(timer);\n",
       "        embed_document(root);\n",
       "      } else {\n",
       "        attempts++;\n",
       "        if (attempts > 100) {\n",
       "          clearInterval(timer);\n",
       "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
       "        }\n",
       "      }\n",
       "    }, 10, root)\n",
       "  }\n",
       "})(window);"
      ],
      "application/vnd.bokehjs_exec.v0+json": ""
     },
     "metadata": {
      "application/vnd.bokehjs_exec.v0+json": {
       "id": "2544"
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 数据\n",
    "N = 4000\n",
    "x = np.random.random(size=N) * 100  # 随机点x坐标\n",
    "y = np.random.random(size=N) * 100  # 随机点y坐标\n",
    "radii = np.random.random(size=N) * 1.5  # 随机半径\n",
    "# 工具条\n",
    "TOOLS=\"hover,crosshair,pan,wheel_zoom,box_zoom,reset,tap,save,box_select,poly_select,lasso_select\"\n",
    "# RGB颜色，画布1，绘图1\n",
    "colors2 = [\"#%02x%02x%02x\" % (int(r), int(g), 150) for r, g in zip(50+2*x, 30+2*y)]\n",
    "p1 = figure(width=300, height=300, tools=TOOLS)\n",
    "p1.scatter(x,y, radius=radii, fill_color=colors2, fill_alpha=0.6, line_color=None)\n",
    "# RGB颜色，画布2，绘图2\n",
    "colors2 = [\"#%02x%02x%02x\" % (150, int(g), int(b)) for g, b in zip(50+2*x, 30+2*y)]\n",
    "p2 = figure(width=300, height=300, tools=TOOLS)\n",
    "p2.scatter(x,y, radius=radii, fill_color=colors2, fill_alpha=0.6, line_color=None)\n",
    "# 直接显示\n",
    "# show(p1)\n",
    "# show(p2)\n",
    "# 网格显示\n",
    "from bokeh.layouts import gridplot\n",
    "grid = gridplot([[p1, p2]]) \n",
    "show(grid)"
   ]
  }
 ],
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   "title_cell": "Table of Contents",
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